diff --git a/src/frontends/tensorflow_common/src/op/pack.cpp b/src/frontends/tensorflow_common/src/op/pack.cpp
index d4502ad75c4..51773bf4725 100644
--- a/src/frontends/tensorflow_common/src/op/pack.cpp
+++ b/src/frontends/tensorflow_common/src/op/pack.cpp
@@ -14,18 +14,21 @@ namespace tensorflow {
 namespace op {
 
 OutputVector translate_pack_op(const NodeContext& node) {
-    auto axis = node.get_attribute<int64_t>("axis");
+    default_op_checks(node, 1, {"Pack", "PACK"});
+    auto num_size = static_cast<int>(node.get_input_size());
+
+    auto axis = node.get_attribute<int64_t>("axis", 0);
     auto axis_const = make_shared<Constant>(element::i64, Shape{}, axis);
 
     OutputVector concat_inputs;
-    for (size_t i = 0; i < node.get_input_size(); ++i) {
-        auto in = node.get_input(static_cast<int>(i));
+    for (int ind = 0; ind < num_size; ++ind) {
+        auto in = node.get_input(ind);
         concat_inputs.push_back(make_shared<Unsqueeze>(in, axis_const));
     }
 
-    auto res = make_shared<Concat>(concat_inputs, axis);
-    set_node_name(node.get_name(), res);
-    return res->outputs();
+    auto pack = make_shared<Concat>(concat_inputs, axis);
+    set_node_name(node.get_name(), pack);
+    return {pack};
 }
 }  // namespace op
 }  // namespace tensorflow
diff --git a/tests/layer_tests/tensorflow_tests/test_tf_Pack.py b/tests/layer_tests/tensorflow_tests/test_tf_Pack.py
new file mode 100644
index 00000000000..cfee54616fc
--- /dev/null
+++ b/tests/layer_tests/tensorflow_tests/test_tf_Pack.py
@@ -0,0 +1,53 @@
+# Copyright (C) 2018-2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+import pytest
+import tensorflow as tf
+from common.tf_layer_test_class import CommonTFLayerTest
+
+
+class TestPack(CommonTFLayerTest):
+    def _prepare_input(self, inputs_info):
+        inputs_data = {}
+        for input_name, input_shape in inputs_info.items():
+            inputs_data[input_name] = np.random.randint(-5, 5, input_shape).astype(self.input_type)
+        return inputs_data
+
+    def create_pack_net(self, input_shape, input_num, axis, input_type):
+        self.input_type = input_type
+        tf.compat.v1.reset_default_graph()
+        # Create the graph and model
+        with tf.compat.v1.Session() as sess:
+            inputs = []
+            type_map = {
+                np.float32: tf.float32,
+                np.int32: tf.int32,
+            }
+            assert input_type in type_map, "Test error: need to update type_map"
+            tf_type = type_map[input_type]
+            for ind in range(input_num):
+                inputs.append(tf.compat.v1.placeholder(tf_type, input_shape, 'input' + str(ind)))
+            if axis is not None:
+                tf.raw_ops.Pack(values=inputs, axis=axis)
+            else:
+                tf.raw_ops.Pack(values=inputs)
+            tf.compat.v1.global_variables_initializer()
+
+            tf_net = sess.graph_def
+
+        return tf_net, None
+
+    test_data_basic = [
+        dict(input_shape=[2, 4], input_num=2, axis=None, input_type=np.float32),
+        dict(input_shape=[3, 1, 2], input_num=3, axis=1, input_type=np.int32),
+    ]
+
+    @pytest.mark.parametrize("params", test_data_basic)
+    @pytest.mark.precommit_tf_fe
+    @pytest.mark.nightly
+    def test_pack_basic(self, params, ie_device, precision, ir_version, temp_dir,
+                        use_new_frontend, use_old_api):
+        self._test(*self.create_pack_net(**params),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                   use_new_frontend=use_new_frontend, use_old_api=use_old_api)