diff --git a/src/frontends/tensorflow_common/src/helper_transforms/embedding_segments_feature_fusing.cpp b/src/frontends/tensorflow_common/src/helper_transforms/embedding_segments_feature_fusing.cpp
index f4cf1b0c02f..91fa1d4be4d 100644
--- a/src/frontends/tensorflow_common/src/helper_transforms/embedding_segments_feature_fusing.cpp
+++ b/src/frontends/tensorflow_common/src/helper_transforms/embedding_segments_feature_fusing.cpp
@@ -91,8 +91,14 @@ ov::frontend::tensorflow::pass::EmbeddingSegmentSingleFeatureFusion::EmbeddingSe
                                         false);
     auto tile = make_shared<Tile>(reshape, pack);
 
-    auto zeros_like = make_shared<Broadcast>(make_shared<Constant>(ov::element::f32, Shape{1}, std::vector<int64_t>{0}),
-                                             make_shared<ShapeOf>(sparse_segment_op));
+    auto zero_int_const = make_shared<Constant>(element::i32, Shape{1}, 0);
+    auto one_int_const = make_shared<Constant>(element::i32, Shape{1}, 1);
+    Output<Node> shape_of = make_shared<ShapeOf>(sparse_segment_op, element::i32);
+    shape_of = make_shared<Concat>(OutputVector{one_int_const, shape_of}, 0);
+
+    Output<Node> zeros_like =
+        make_shared<Broadcast>(make_shared<Constant>(ov::element::f32, Shape{1}, std::vector<int64_t>{0}), shape_of);
+    zeros_like = make_shared<Squeeze>(zeros_like, zero_int_const);
 
     // compute number of dimensions to unsqueeze the condition
     auto cond_rank = compute_subgraph_scalar_rank(tile, element::i32);
diff --git a/src/frontends/tensorflow_common/src/op/zeros_like.cpp b/src/frontends/tensorflow_common/src/op/zeros_like.cpp
index 4baf3ec49f0..19f794e7b01 100644
--- a/src/frontends/tensorflow_common/src/op/zeros_like.cpp
+++ b/src/frontends/tensorflow_common/src/op/zeros_like.cpp
@@ -14,12 +14,25 @@ namespace tensorflow {
 namespace op {
 
 OutputVector translate_zeros_like_op(const NodeContext& node) {
+    default_op_checks(node, 1, {"ZerosLike", "ZEROS_LIKE"});
     auto x = node.get_input(0);
-    auto shape_of = make_shared<ShapeOf>(x);
-    auto zero = make_shared<Constant>(x.get_element_type(), Shape{1}, 0);
-    auto res = make_shared<Broadcast>(zero, shape_of);
-    set_node_name(node.get_name(), res);
-    return res->outputs();
+    Output<Node> shape_of = make_shared<ShapeOf>(x, element::i32);
+    auto zero_const = make_shared<Constant>(x.get_element_type(), Shape{1}, 0);
+
+    // in case of x to be scalar, we need handle it more specifically
+    // since Broadcast supports only broadcasting to rank greater 0
+    // we have to introduce extra dimension for input scalar case
+    auto zero_int_const = make_shared<Constant>(element::i32, Shape{1}, 0);
+    auto one_int_const = make_shared<Constant>(element::i32, Shape{1}, 1);
+    shape_of = make_shared<Concat>(OutputVector{one_int_const, shape_of}, 0);
+
+    // create a tensor of zeros of shape with extra dimension
+    Output<Node> zeros_like = make_shared<Broadcast>(zero_const, shape_of);
+    // remove extra dimension by squeezing
+    zeros_like = make_shared<Squeeze>(zeros_like, zero_int_const);
+
+    set_node_name(node.get_name(), zeros_like.get_node_shared_ptr());
+    return {zeros_like};
 }
 
 }  // namespace op
diff --git a/tests/layer_tests/tensorflow_tests/test_tf_ZerosLike.py b/tests/layer_tests/tensorflow_tests/test_tf_ZerosLike.py
new file mode 100644
index 00000000000..ad8ba15a383
--- /dev/null
+++ b/tests/layer_tests/tensorflow_tests/test_tf_ZerosLike.py
@@ -0,0 +1,35 @@
+# Copyright (C) 2018-2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import pytest
+import tensorflow as tf
+from common.tf_layer_test_class import CommonTFLayerTest
+
+
+class TestZerosLike(CommonTFLayerTest):
+    def create_zeros_like_net(self, x_shape):
+        tf.compat.v1.reset_default_graph()
+        # Create the graph and model
+        with tf.compat.v1.Session() as sess:
+            x = tf.compat.v1.placeholder(tf.float32, x_shape, 'x')
+            tf.raw_ops.ZerosLike(x=x)
+            tf.compat.v1.global_variables_initializer()
+            tf_net = sess.graph_def
+
+        return tf_net, None
+
+    test_data_basic = [
+        dict(x_shape=[]),
+        dict(x_shape=[3]),
+        dict(x_shape=[2, 1, 4]),
+        dict(x_shape=[2, 4, 3, 1]),
+    ]
+
+    @pytest.mark.parametrize("params", test_data_basic)
+    @pytest.mark.precommit_tf_fe
+    @pytest.mark.nightly
+    def test_zeros_like_basic(self, params, ie_device, precision, ir_version, temp_dir,
+                              use_new_frontend, use_old_api):
+        self._test(*self.create_zeros_like_net(**params),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                   use_new_frontend=use_new_frontend, use_old_api=use_old_api)