diff --git a/src/common/transformations/src/transformations/op_conversions/einsum_decomposition.cpp b/src/common/transformations/src/transformations/op_conversions/einsum_decomposition.cpp
index b58b58b57ae5d2..35cc48253b0e1e 100644
--- a/src/common/transformations/src/transformations/op_conversions/einsum_decomposition.cpp
+++ b/src/common/transformations/src/transformations/op_conversions/einsum_decomposition.cpp
@@ -322,22 +322,24 @@ ov::Output<ov::Node> unsqueeze_input(const ov::Output<ov::Node>& input_node,
 ov::OutputVector broadcast_merge_shapes(ov::OutputVector& shapes_lhs,
                                         ov::OutputVector& shapes_rhs,
                                         ov::NodeVector& subgraph_nodes) {
-    // TODO - Refactor func to remove loop and duplicated Broadcast.
-    OPENVINO_ASSERT(shapes_lhs.size() == shapes_rhs.size());
-    ov::OutputVector broadcasted_shape_nodes{shapes_lhs.size()};
-
-    for (size_t shp_i = 0; shp_i < shapes_lhs.size(); shp_i++) {
+    ov::OutputVector broadcasted_shape_nodes{};
+    // OutputVector is either empty or contains a single shape
+    if (shapes_lhs.size() == 1 && shapes_rhs.size() == 1) {
         auto const_1 = ov::op::v0::Constant::create(ov::element::Type_t::i64, ov::Shape{1}, {1});
         auto tmp_const_of_lhs_shp =
-            std::make_shared<ov::op::v3::Broadcast>(const_1, shapes_lhs[shp_i], ov::op::BroadcastType::NUMPY);
+            std::make_shared<ov::op::v3::Broadcast>(const_1, shapes_lhs[0], ov::op::BroadcastType::NUMPY);
         auto tmp_const_of_broadcasted_shp =
             std::make_shared<ov::op::v3::Broadcast>(tmp_const_of_lhs_shp,
-                                                    shapes_rhs[shp_i],
+                                                    shapes_rhs[0],
                                                     ov::op::BroadcastType::BIDIRECTIONAL);
         auto broadcasted_shape = std::make_shared<ov::op::v3::ShapeOf>(tmp_const_of_broadcasted_shp);
-        broadcasted_shape_nodes[shp_i] = broadcasted_shape;
+        broadcasted_shape_nodes.push_back(broadcasted_shape->output(0));
         subgraph_nodes.insert(subgraph_nodes.end(),
                               {const_1, tmp_const_of_lhs_shp, tmp_const_of_broadcasted_shp, broadcasted_shape});
+    } else if (shapes_lhs.size() == 0 && shapes_rhs.size() == 1) {
+        return shapes_rhs;
+    } else if (shapes_lhs.size() == 1 && shapes_rhs.size() == 0) {
+        return shapes_lhs;
     }
     return broadcasted_shape_nodes;
 }