diff --git a/src/frontends/onnx/tests/models/softmax_crossentropy_loss_higher_dim.prototxt b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_higher_dim.prototxt
new file mode 100644
index 00000000000000..52cda8520df3b1
--- /dev/null
+++ b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_higher_dim.prototxt
@@ -0,0 +1,55 @@
+ir_version: 7
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "x"
+    input: "y"
+    output: "z"
+    op_type: "SoftmaxCrossEntropyLoss"
+    attribute {
+      name: "reduction"
+      s: "mean"
+      type: STRING
+    }
+  }
+  name: "test_sce_higher_dim"
+  input {
+    name: "x"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 3 }
+          dim { dim_value: 2 }
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  input {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 7
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 2 }
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  output {
+    name: "z"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {}
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}
\ No newline at end of file
diff --git a/src/frontends/onnx/tests/models/softmax_crossentropy_loss_mean_weight_ii.prototxt b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_mean_weight_ii.prototxt
new file mode 100644
index 00000000000000..c0e2d1e893d0f3
--- /dev/null
+++ b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_mean_weight_ii.prototxt
@@ -0,0 +1,70 @@
+ir_version: 7
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "x"
+    input: "y"
+    input: "w"
+    output: "z"
+    op_type: "SoftmaxCrossEntropyLoss"
+    attribute {
+      name: "reduction"
+      s: "mean"
+      type: STRING
+    }
+    attribute {
+      name: "ignore_index"
+      i: -1
+      type: INT
+    }
+  }
+  name: "test_sce_mean_weight_ii"
+  input {
+    name: "x"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 3 }
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  input {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 7
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  input {
+    name: "w"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 3 }
+        }
+      }
+    }
+  }
+  output {
+    name: "z"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {}
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}
\ No newline at end of file
diff --git a/src/frontends/onnx/tests/models/softmax_crossentropy_loss_none.prototxt b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_none.prototxt
new file mode 100644
index 00000000000000..6b81cf2cf41d97
--- /dev/null
+++ b/src/frontends/onnx/tests/models/softmax_crossentropy_loss_none.prototxt
@@ -0,0 +1,53 @@
+ir_version: 7
+producer_name: "OpenVINO ONNX Frontend"
+graph {
+  node {
+    input: "x"
+    input: "y"
+    output: "z"
+    op_type: "SoftmaxCrossEntropyLoss"
+    attribute {
+      name: "reduction"
+      s: "none"
+      type: STRING
+    }
+  }
+  name: "test_sce_none"
+  input {
+    name: "x"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 2 }
+          dim { dim_value: 3 }
+        }
+      }
+    }
+  }
+  input {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 7
+        shape {
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+  output {
+    name: "z"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim { dim_value: 2 }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 13
+}
\ No newline at end of file
diff --git a/src/frontends/onnx/tests/onnx_import.in.cpp b/src/frontends/onnx/tests/onnx_import.in.cpp
index 36155f43ed9d6a..0253fc3989e0e2 100644
--- a/src/frontends/onnx/tests/onnx_import.in.cpp
+++ b/src/frontends/onnx/tests/onnx_import.in.cpp
@@ -6949,9 +6949,45 @@ OPENVINO_TEST(${BACKEND_NAME}, onnx_float8e4m3fn_constant) {
 OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_sum) {
     auto model = convert_model("softmax_crossentropy_loss_sum.onnx");
     auto test_case = ov::test::TestCase(model, s_device);
+
     test_case.add_input<float>({0.5f, 1.5f, 2.5f, 3.5f, 4.5f, 5.5f});
     test_case.add_input<int64_t>({1, 2});
-    test_case.add_expected_output<float>(Shape{}, {1.81521f});
 
+    test_case.add_expected_output<float>(Shape{}, {1.81521f});
     test_case.run_with_tolerance_as_fp(0.0015f);
 }
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_mean_weight_ii) {
+    auto model = convert_model("softmax_crossentropy_loss_mean_weight_ii.onnx");
+    auto test_case = ov::test::TestCase(model, s_device);
+    
+    test_case.add_input<float>({1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f, 12.f});
+    test_case.add_input<int64_t>({0, -1, 2, 1});
+    test_case.add_input<float>({0.5f, 1.0f, 2.0f});
+
+    test_case.add_expected_output<float>(Shape{}, {1.2857887f});
+    test_case.run_with_tolerance_as_fp(0.001f);
+}
+
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_none) {
+    auto model = convert_model("softmax_crossentropy_loss_none.onnx");
+    auto test_case = ov::test::TestCase(model, s_device);
+
+    test_case.add_input<float>({1.f, 2.f, 3.f, 4.f, 5.f, 6.f});
+    test_case.add_input<int64_t>({2, 1});
+
+    test_case.add_expected_output<float>(Shape{2}, {0.40760595f, 1.4076059f});
+    test_case.run_with_tolerance_as_fp(0.001f);
+}
+
+OPENVINO_TEST(${BACKEND_NAME}, onnx_model_softmax_crossentropy_loss_higher_dim) {
+    auto model = convert_model("softmax_crossentropy_loss_higher_dim.onnx");
+    auto test_case = ov::test::TestCase(model, s_device);
+
+    test_case.add_input<float>(std::vector<float>(24, 1.0f));
+    test_case.add_input<int64_t>({1, 0, 2, 1, 0, 2, 1, 1});
+
+    test_case.add_expected_output<float>(Shape{}, {1.0986123f});
+    test_case.run_with_tolerance_as_fp(0.001f);
+}