diff --git a/src/common/transformations/src/transformations/common_optimizations/simplify_shape_of_sub_graph.cpp b/src/common/transformations/src/transformations/common_optimizations/simplify_shape_of_sub_graph.cpp
index 8b9a1c3de9f..14dede1e6f8 100644
--- a/src/common/transformations/src/transformations/common_optimizations/simplify_shape_of_sub_graph.cpp
+++ b/src/common/transformations/src/transformations/common_optimizations/simplify_shape_of_sub_graph.cpp
@@ -20,6 +20,9 @@
 
 NGRAPH_RTTI_DEFINITION(ngraph::pass::SharedShapeOf, "SharedShapeOf", 0);
 
+static constexpr size_t index_for_int32 = 0;
+static constexpr size_t index_for_int64 = 1;
+
 bool ngraph::pass::SharedShapeOf::run_on_model(const std::shared_ptr<ngraph::Function>& f) {
     RUN_ON_FUNCTION_SCOPE(SharedShapeOf);
     bool graph_rewritten = false;
@@ -38,10 +41,21 @@ bool ngraph::pass::SharedShapeOf::run_on_model(const std::shared_ptr<ngraph::Fun
     for (const auto& pair : source_to_shape_of) {
         if (pair.second.size() < 2)
             continue;
-        const auto& root_ss = pair.second[0];
-        for (const auto& child_ss : pair.second)
-            if (root_ss->get_instance_id() != child_ss->get_instance_id() && root_ss->get_output_element_type(0) == root_ss->get_output_element_type(0))
-                graph_rewritten |= replace_output_update_name(child_ss->output(0), root_ss->output(0));
+
+        NodeVector nodes_for_different_types[2];
+        for (const auto& child : pair.second) {
+            const auto& type_of_output = child->get_output_element_type(0);
+            size_t index = (type_of_output == element::i32) ? index_for_int32 : index_for_int64;
+            nodes_for_different_types[index].push_back(child);
+        }
+        for (const auto& v : nodes_for_different_types) {
+            if (v.empty())
+                continue;
+            const auto& root_ss = v[0];
+            for (const auto& child_ss : v)
+                if (root_ss->get_instance_id() != child_ss->get_instance_id())
+                    graph_rewritten |= replace_output_update_name(child_ss->output(0), root_ss->output(0));
+        }
     }
     return graph_rewritten;
 }
diff --git a/src/tests/functional/inference_engine/transformations/shared_shapeof_test.cpp b/src/tests/functional/inference_engine/transformations/shared_shapeof_test.cpp
new file mode 100644
index 00000000000..a6585b6cb92
--- /dev/null
+++ b/src/tests/functional/inference_engine/transformations/shared_shapeof_test.cpp
@@ -0,0 +1,178 @@
+// Copyright (C) 2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include <gtest/gtest.h>
+
+#include <string>
+#include <memory>
+
+#include <ngraph/function.hpp>
+#include <ngraph/opsets/opset1.hpp>
+#include <ngraph/opsets/opset8.hpp>
+#include <ngraph/pass/manager.hpp>
+#include <ngraph/pass/visualize_tree.hpp>
+#include <transformations/common_optimizations/simplify_shape_of_sub_graph.hpp>
+#include <transformations/init_node_info.hpp>
+#include <transformations/utils/utils.hpp>
+
+#include "common_test_utils/ngraph_test_utils.hpp"
+
+using namespace testing;
+
+TEST_F(TransformationTestsF, SharedShapeOfTest) {
+    ngraph::Shape input_shape { 120, 4 };
+    {
+        auto input = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32, input_shape);
+
+        auto shapeof1_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof2_i64 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i64);
+        auto shapeof3_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof4_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof5_i64 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i64);
+        auto shapeof6_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof7_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+
+        auto shapeof1_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof3_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof3_i32, ngraph::element::i64);
+        auto shapeof4_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof4_i32, ngraph::element::i64);
+        auto shapeof6_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof6_i32, ngraph::element::i64);
+        auto shapeof7_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof7_i32, ngraph::element::i64);
+
+        ngraph::OutputVector inputs_of_concat {shapeof1_i32_convert, shapeof2_i64, shapeof3_i32_convert, shapeof4_i32_convert,
+                                               shapeof5_i64, shapeof6_i32_convert, shapeof7_i32_convert};
+
+        auto concat = std::make_shared<ngraph::opset8::Concat>(inputs_of_concat, 0);
+        function = std::make_shared<ngraph::Function>(ngraph::NodeVector{ concat }, ngraph::ParameterVector{ input });
+        manager.register_pass<ngraph::pass::SharedShapeOf>();
+    }
+    {
+        auto input = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32, input_shape);
+
+        auto shapeof1_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof2_i64 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i64);
+
+        auto shapeof1_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof3_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof4_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof6_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof7_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+
+        ngraph::OutputVector inputs_of_concat {shapeof1_i32_convert, shapeof2_i64, shapeof3_i32_convert, shapeof4_i32_convert,
+                                               shapeof2_i64, shapeof6_i32_convert, shapeof7_i32_convert};
+
+        auto concat = std::make_shared<ngraph::opset8::Concat>(inputs_of_concat, 0);
+        function_ref = std::make_shared<ngraph::Function>(ngraph::NodeVector{ concat }, ngraph::ParameterVector{ input });
+    }
+}
+
+TEST_F(TransformationTestsF, SharedShapeOfTestI64Only) {
+    ngraph::Shape input_shape { 120, 4 };
+    {
+        auto input = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32, input_shape);
+
+        auto shapeof1_i64 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i64);
+        auto shapeof2_i64 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i64);
+        auto shapeof3_i64 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i64);
+
+        ngraph::OutputVector inputs_of_concat {shapeof1_i64, shapeof2_i64, shapeof3_i64};
+
+        auto concat = std::make_shared<ngraph::opset8::Concat>(inputs_of_concat, 0);
+        function = std::make_shared<ngraph::Function>(ngraph::NodeVector{ concat }, ngraph::ParameterVector{ input });
+        manager.register_pass<ngraph::pass::SharedShapeOf>();
+    }
+    {
+        auto input = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32, input_shape);
+        auto shapeof1_i64 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i64);
+
+        ngraph::OutputVector inputs_of_concat {shapeof1_i64, shapeof1_i64, shapeof1_i64};
+
+        auto concat = std::make_shared<ngraph::opset8::Concat>(inputs_of_concat, 0);
+        function_ref = std::make_shared<ngraph::Function>(ngraph::NodeVector{ concat }, ngraph::ParameterVector{ input });
+    }
+}
+
+TEST_F(TransformationTestsF, SharedShapeOfTestI32Only) {
+    ngraph::Shape input_shape { 120, 4 };
+    {
+        auto input = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32, input_shape);
+
+        auto shapeof1_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof2_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof3_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof4_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof5_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+
+        auto shapeof1_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof2_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof2_i32, ngraph::element::i64);
+        auto shapeof3_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof3_i32, ngraph::element::i64);
+        auto shapeof4_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof4_i32, ngraph::element::i64);
+        auto shapeof5_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof5_i32, ngraph::element::i64);
+
+        ngraph::OutputVector inputs_of_concat {shapeof1_i32_convert, shapeof2_i32_convert, shapeof3_i32_convert,
+                                               shapeof4_i32_convert, shapeof5_i32_convert};
+
+        auto concat = std::make_shared<ngraph::opset8::Concat>(inputs_of_concat, 0);
+        function = std::make_shared<ngraph::Function>(ngraph::NodeVector{ concat }, ngraph::ParameterVector{ input });
+        manager.register_pass<ngraph::pass::SharedShapeOf>();
+    }
+    {
+        auto input = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32, input_shape);
+
+        auto shapeof1_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+
+        auto shapeof1_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof2_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof3_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof4_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+        auto shapeof5_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof1_i32, ngraph::element::i64);
+
+        ngraph::OutputVector inputs_of_concat {shapeof1_i32_convert, shapeof2_i32_convert, shapeof3_i32_convert,
+                                               shapeof4_i32_convert, shapeof5_i32_convert};
+
+        auto concat = std::make_shared<ngraph::opset8::Concat>(inputs_of_concat, 0);
+        function_ref = std::make_shared<ngraph::Function>(ngraph::NodeVector{ concat }, ngraph::ParameterVector{ input });
+    }
+}
+
+TEST_F(TransformationTestsF, SharedShapeOfTestMixed) {
+    ngraph::Shape input_shape { 120, 4 };
+    {
+        auto input = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32, input_shape);
+
+        auto shapeof1 = std::make_shared<ngraph::opset1::ShapeOf>(input);
+        auto shapeof2_i64 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i64);
+        auto shapeof3_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof4 = std::make_shared<ngraph::opset1::ShapeOf>(input);
+        auto shapeof5_i64 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i64);
+        auto shapeof6_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+        auto shapeof7_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+
+        auto shapeof3_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof3_i32, ngraph::element::i64);
+        auto shapeof6_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof6_i32, ngraph::element::i64);
+        auto shapeof7_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof7_i32, ngraph::element::i64);
+
+        ngraph::OutputVector inputs_of_concat {shapeof1, shapeof2_i64, shapeof3_i32_convert, shapeof4,
+                                               shapeof5_i64, shapeof6_i32_convert, shapeof7_i32_convert};
+
+        auto concat = std::make_shared<ngraph::opset8::Concat>(inputs_of_concat, 0);
+        function = std::make_shared<ngraph::Function>(ngraph::NodeVector{ concat }, ngraph::ParameterVector{ input });
+        manager.register_pass<ngraph::pass::SharedShapeOf>();
+    }
+    {
+        auto input = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32, input_shape);
+
+        auto shapeof1 = std::make_shared<ngraph::opset1::ShapeOf>(input);
+        auto shapeof2_i32 = std::make_shared<ngraph::opset8::ShapeOf>(input, ngraph::element::i32);
+
+        auto shapeof3_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof2_i32, ngraph::element::i64);
+        auto shapeof6_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof2_i32, ngraph::element::i64);
+        auto shapeof7_i32_convert = std::make_shared<ngraph::opset8::Convert>(shapeof2_i32, ngraph::element::i64);
+
+        ngraph::OutputVector inputs_of_concat {shapeof1, shapeof1, shapeof3_i32_convert, shapeof1,
+                                               shapeof1, shapeof6_i32_convert, shapeof7_i32_convert};
+
+        auto concat = std::make_shared<ngraph::opset8::Concat>(inputs_of_concat, 0);
+        function_ref = std::make_shared<ngraph::Function>(ngraph::NodeVector{ concat }, ngraph::ParameterVector{ input });
+    }
+}
diff --git a/tools/mo/openvino/tools/mo/ops/select.py b/tools/mo/openvino/tools/mo/ops/select.py
index 3d3520638a1..fa27e1f1c7e 100644
--- a/tools/mo/openvino/tools/mo/ops/select.py
+++ b/tools/mo/openvino/tools/mo/ops/select.py
@@ -50,6 +50,8 @@ class Select(Op):
             output_shape = bi_directional_shape_broadcasting(a_shape, b_shape)
             assert output_shape is not None, msg
 
+            output_is_scalar = len(output_shape) == 0
+
             # if Select was created from TF Where operations then 1D condition must have the same size
             # as 0-index dimension of output_shape. This condition is different from being numpy compatible
             # but by adding ones to the end we can achieve numpy compatibility, as in transformation SelectBroadcast.py
@@ -61,9 +63,10 @@ class Select(Op):
                             node_name, condition_shape, a_shape, b_shape)
 
                 # check equality only if both values non-dynamic
-                if is_fully_defined(condition_shape[0]) and is_fully_defined(output_shape[0]):
+                if is_fully_defined(condition_shape[0]) and not output_is_scalar and is_fully_defined(output_shape[0]):
                     assert condition_shape[0] == output_shape[0], msg_tf
-                condition_shape = np.concatenate((condition_shape, np.ones(len(output_shape) - 1)))
+                ones_shape = len(output_shape) if output_is_scalar else len(output_shape) - 1
+                condition_shape = np.concatenate((condition_shape, np.ones(ones_shape)))
 
             output_shape = bi_directional_shape_broadcasting(output_shape, condition_shape)
             assert output_shape is not None, msg
diff --git a/tools/mo/unit_tests/mo/ops/select_test.py b/tools/mo/unit_tests/mo/ops/select_test.py
index 0b6e5671405..f5e49420dd4 100644
--- a/tools/mo/unit_tests/mo/ops/select_test.py
+++ b/tools/mo/unit_tests/mo/ops/select_test.py
@@ -100,6 +100,34 @@ class TestSelect(unittest.TestCase):
                                                       out_value=np.ones([15, 3, 5], dtype=np.float))
         self.assertTrue(flag, msg)
 
+    def test_select_infer_condition_true_then_and_else_are_scalars(self):
+        flag, msg = self.build_select_graph_and_infer(condition_value=np.array([True], dtype=bool),
+                                                      then_value=np.array(3, dtype=np.float),
+                                                      else_value=np.array(1, dtype=np.float),
+                                                      out_value=np.array([3], dtype=np.float))
+        self.assertTrue(flag, msg)
+
+    def test_select_infer_condition_true_then_and_else_are_scalars_2(self):
+        flag, msg = self.build_select_graph_and_infer(condition_value=np.array(True, dtype=bool),
+                                                      then_value=np.array(3, dtype=np.float),
+                                                      else_value=np.array(1, dtype=np.float),
+                                                      out_value=np.array(3, dtype=np.float))
+        self.assertTrue(flag, msg)
+
+    def test_select_infer_condition_false_then_and_else_are_scalars(self):
+        flag, msg = self.build_select_graph_and_infer(condition_value=np.array([False], dtype=bool),
+                                                      then_value=np.array(3, dtype=np.float),
+                                                      else_value=np.array(1, dtype=np.float),
+                                                      out_value=np.array([1], dtype=np.float))
+        self.assertTrue(flag, msg)
+
+    def test_select_infer_condition_false_then_and_else_are_scalars_2(self):
+        flag, msg = self.build_select_graph_and_infer(condition_value=np.array(False, dtype=bool),
+                                                      then_value=np.array(3, dtype=np.float),
+                                                      else_value=np.array(1, dtype=np.float),
+                                                      out_value=np.array(1, dtype=np.float))
+        self.assertTrue(flag, msg)
+
     def test_select_infer_condition_false_2(self):
         flag, msg = self.build_select_graph_and_infer(condition_value=np.array([False], dtype=bool),
                                                       then_value=np.ones([15, 3, 5], dtype=np.float),