diff --git a/src/core/include/openvino/core/partial_shape.hpp b/src/core/include/openvino/core/partial_shape.hpp
index 78574e5d2e7..9a70b72867d 100644
--- a/src/core/include/openvino/core/partial_shape.hpp
+++ b/src/core/include/openvino/core/partial_shape.hpp
@@ -32,6 +32,7 @@ class OPENVINO_API PartialShape {
     using Dimensions = std::vector<Dimension>;
 
 public:
+    using value_type = Dimensions::value_type;
     using iterator = Dimensions::iterator;
     using const_iterator = Dimensions::const_iterator;
     using reverse_iterator = Dimensions::reverse_iterator;
@@ -342,6 +343,13 @@ public:
         m_rank_is_static = true;
         m_shape_type = ShapeType::SHAPE_IS_UPDATED;
     }
+    /// \brief emplace element to the end of partial shape
+    template <class... Args>
+    void emplace_back(Args&&... args) {
+        m_dimensions.emplace_back(std::forward<Args>(args)...);
+        m_rank_is_static = true;
+        m_shape_type = ShapeType::SHAPE_IS_UPDATED;
+    }
 
     /// \brief String representation of PartialShape
     std::string to_string() const;
diff --git a/src/core/shape_inference/include/squeeze_shape_inference.hpp b/src/core/shape_inference/include/squeeze_shape_inference.hpp
index 27a1737659d..c33ebf74677 100644
--- a/src/core/shape_inference/include/squeeze_shape_inference.hpp
+++ b/src/core/shape_inference/include/squeeze_shape_inference.hpp
@@ -32,6 +32,7 @@ void shape_infer(const Squeeze* op,
     const auto number_of_inputs = input_shapes.size();
 
     const auto& arg_shape = input_shapes[0];
+    const auto& arg_rank = arg_shape.rank();
     auto& output_shape = output_shapes[0];
 
     std::unique_ptr<std::set<int64_t>> unique_axes;
@@ -46,9 +47,8 @@ void shape_infer(const Squeeze* op,
                               axes_shape.rank().get_length());
 
         std::vector<int64_t> axes;
-        if (arg_shape.rank().is_static() && axes_shape.is_static() &&
-            get_data_as_int64<T>(1, op, axes, constant_data)) {
-            normalize_axes(op, arg_shape.rank().get_length(), axes);
+        if (arg_rank.is_static() && axes_shape.is_static() && get_data_as_int64<T>(1, op, axes, constant_data)) {
+            normalize_axes(op, arg_rank.get_length(), axes);
             unique_axes.reset(new std::set<int64_t>(axes.cbegin(), axes.cend()));
         }
     } else {
@@ -56,16 +56,18 @@ void shape_infer(const Squeeze* op,
         NODE_VALIDATION_CHECK(op, false);
     }
 
-    if (arg_shape.rank().is_static() && (unique_axes != nullptr)) {
-        std::vector<DimType> out_dims;
-        out_dims.reserve(arg_shape.rank().get_length());
+    if (arg_rank.is_static() && (unique_axes != nullptr)) {
+        output_shape.resize(0);
 
         if (unique_axes->empty()) {
             // According to specification, if only first input provided` or axes are empty
             // remove all dimensions equal to 1.
-            std::copy_if(arg_shape.cbegin(), arg_shape.cend(), back_inserter(out_dims), [](const DimType& dim) {
-                return !dim.compatible(1);
-            });
+            std::copy_if(arg_shape.cbegin(),
+                         arg_shape.cend(),
+                         std::back_inserter(output_shape),
+                         [](const DimType& dim) {
+                             return !dim.compatible(1);
+                         });
         } else {
             int64_t idx = 0;
             auto rm_axis_iter = unique_axes->cbegin();
@@ -84,16 +86,17 @@ void shape_infer(const Squeeze* op,
                 }
             };
 
-            std::copy_if(arg_shape.cbegin(), arg_shape.cend(), back_inserter(out_dims), not_squeezable_at_axis);
+            std::copy_if(arg_shape.cbegin(),
+                         arg_shape.cend(),
+                         std::back_inserter(output_shape),
+                         not_squeezable_at_axis);
+        }
+        // When arg shape has got static rank but shape is dynamic and output shape dimensions is empty (scalar)
+        // make dynamic output except the case when arg_shape is 1-D shape with 0 or 1 element then should be scalar.
+        if (arg_shape.is_dynamic() && (output_shape.size() == 0) &&
+            !(arg_rank.get_length() == 1 && arg_shape[0].get_max_length() <= 1)) {
+            output_shape = PartialShape::dynamic();
         }
-        // When arg shape has got static rank but shape is dynamic and output shape dimensions is empty
-        // make dynamic output except the case of the rank of arg shape is 1 and 0 <= arg_shape[0] <= 1.
-        if (arg_shape.is_dynamic() && out_dims.empty()) {
-            output_shape = arg_shape.rank().get_length() == 1 && arg_shape[0].get_max_length() <= 1
-                               ? T{}  // Output shape is a scalar
-                               : PartialShape::dynamic();
-        } else
-            output_shape = T(out_dims);
     } else {
         output_shape = PartialShape::dynamic();
     }
diff --git a/src/core/tests/partial_shape.cpp b/src/core/tests/partial_shape.cpp
index 5e15fe230c1..4689e833217 100644
--- a/src/core/tests/partial_shape.cpp
+++ b/src/core/tests/partial_shape.cpp
@@ -782,6 +782,22 @@ TEST(partial_shape, changed_dimension_by_reference) {
     ASSERT_TRUE(s.is_static());
 }
 
+TEST(partial_shape, emplace_back_new_dimension) {
+    PartialShape s{2, 3, Dimension::dynamic(), 5};
+
+    s.emplace_back(3, 5);
+
+    ASSERT_EQ(s, PartialShape({2, 3, -1, 5, {3, 5}}));
+}
+
+TEST(partial_shape, copy_with_back_inserter_iterator) {
+    PartialShape s{2, 3, Dimension::dynamic(), 5}, s_copy;
+
+    std::copy(s.begin(), s.end(), std::back_inserter(s_copy));
+
+    ASSERT_EQ(s_copy, s);
+}
+
 TEST(partial_shape, infer_windowed_reduction_rank_dynamic_rank_dynamic_ok) {
     auto node = std::make_shared<op::Parameter>(element::f32, Shape{});
     PartialShape data_shape{PartialShape::dynamic()};