diff --git a/tests/layer_tests/tensorflow_tests/test_tf_Bucketize.py b/tests/layer_tests/tensorflow_tests/test_tf_Bucketize.py
index a1a4e4fadce..bf0c2ef7bc3 100644
--- a/tests/layer_tests/tensorflow_tests/test_tf_Bucketize.py
+++ b/tests/layer_tests/tensorflow_tests/test_tf_Bucketize.py
@@ -4,90 +4,43 @@
 import numpy as np
 import pytest
 import tensorflow as tf
-from common.layer_test_class import check_ir_version
 from common.tf_layer_test_class import CommonTFLayerTest
 
-from unit_tests.utils.graph import build_graph
-
 
 class TestBucketize(CommonTFLayerTest):
-    def create_bucketize_net(self, input_shape, input_type, boundaries_size, ir_version,
-                             use_new_frontend):
-        """
-            Tensorflow net:                     IR net:
-                 Input            =>      Input        Boundaries
-                   |                           \       /
-               Bucketize                       Bucketize
-           {attrs: boundaries}
-        """
+    def _prepare_input(self, inputs_info):
+        assert 'input' in inputs_info, "Test error: inputs_info must contain `input`"
+        input_shape = inputs_info['input']
+        input_type = self.input_type
+        inputs_data = {}
+        input_data = np.random.randint(-20, 20, input_shape).astype(input_type)
+        inputs_data['input'] = input_data
+        return inputs_data
 
+    def create_bucketize_net(self, input_shape, input_type, boundaries_size):
+        self.input_type = input_type
         tf.compat.v1.reset_default_graph()
         with tf.compat.v1.Session() as sess:
-            x = tf.compat.v1.placeholder(input_type, input_shape, 'Input')
-            constant_value = np.arange(-boundaries_size * 5, boundaries_size * 5, 10,
-                                       dtype=np.float32)
-            # TODO: Bucketize is not tested here. Need to re-write the test
+            input = tf.compat.v1.placeholder(input_type, input_shape, 'input')
+            # generate boundaries list
+            boundaries = np.sort(np.unique(np.random.randint(-200, 200, [boundaries_size]).astype(np.float32))).tolist()
+            tf.raw_ops.Bucketize(input=input, boundaries=boundaries)
             tf.compat.v1.global_variables_initializer()
             tf_net = sess.graph_def
 
-        # create reference IR net
-        ref_net = None
+        return tf_net, None
 
-        if check_ir_version(10, None, ir_version) and not use_new_frontend:
-            nodes_attributes = {
-                'input': {'kind': 'op', 'type': 'Parameter'},
-                'input_data': {'shape': input_shape, 'kind': 'data'},
-                'boundaries_input_data': {'shape': constant_value.shape, 'kind': 'data'},
-                'boundaries': {'type': 'Const', 'kind': 'op'},
-                'boundaries_data': {'kind': 'data', 'shape': constant_value.shape},
-                'bucketize': {'kind': 'op', 'type': 'Bucketize'},
-                'bucketize_data': {'shape': input_shape, 'kind': 'data'},
-                'result': {'kind': 'op', 'type': 'Result'}
-            }
+    test_data_basic = [
+        dict(input_shape=[5], input_type=np.int32, boundaries_size=1),
+        dict(input_shape=[3, 4], input_type=np.float32, boundaries_size=0),
+        dict(input_shape=[2, 3, 4], input_type=np.float32, boundaries_size=300),
+    ]
 
-            ref_net = build_graph(nodes_attributes,
-                                  [('input', 'input_data'),
-                                   ('input_data', 'bucketize', {'in': 0}),
-                                   ('boundaries_input_data', 'boundaries'),
-                                   ('boundaries', 'boundaries_data'),
-                                   ('boundaries_data', 'bucketize', {'in': 1}),
-                                   ('bucketize', 'bucketize_data'),
-                                   ('bucketize_data', 'result')
-                                   ])
-
-        return tf_net, ref_net
-
-    test_data_float32 = [
-        dict(input_shape=[5], input_type=tf.float32, boundaries_size=1),
-        dict(input_shape=[5], input_type=tf.float32, boundaries_size=3),
-        pytest.param(dict(input_shape=[4, 8], input_type=tf.float32, boundaries_size=5),
-                     marks=pytest.mark.precommit_tf_fe),
-        dict(input_shape=[2, 4, 7], input_type=tf.float32, boundaries_size=10),
-        dict(input_shape=[2, 4, 7, 8], input_type=tf.float32, boundaries_size=12),
-        dict(input_shape=[2, 4, 7, 8, 10], input_type=tf.float32, boundaries_size=14)]
-
-    @pytest.mark.parametrize("params", test_data_float32)
+    @pytest.mark.parametrize("params", test_data_basic)
+    @pytest.mark.precommit_tf_fe
     @pytest.mark.nightly
-    def test_bucketize_float32(self, params, ie_device, precision, ir_version, temp_dir,
-                               use_new_frontend, use_old_api):
-        self._test(*self.create_bucketize_net(**params, ir_version=ir_version,
-                                              use_new_frontend=use_new_frontend),
-                   ie_device, precision, ir_version, temp_dir=temp_dir,
-                   use_new_frontend=use_new_frontend, use_old_api=use_old_api)
-
-    test_data_int32 = [
-        dict(input_shape=[5], input_type=tf.int32, boundaries_size=1),
-        dict(input_shape=[5], input_type=tf.int32, boundaries_size=3),
-        dict(input_shape=[4, 8], input_type=tf.int32, boundaries_size=5),
-        dict(input_shape=[2, 4, 7], input_type=tf.int32, boundaries_size=10),
-        dict(input_shape=[2, 4, 7, 8], input_type=tf.float32, boundaries_size=12),
-        dict(input_shape=[2, 4, 7, 8, 10], input_type=tf.float32, boundaries_size=14)]
-
-    @pytest.mark.parametrize("params", test_data_int32)
-    @pytest.mark.nightly
-    def test_bucketize_int32(self, params, ie_device, precision, ir_version, temp_dir,
+    def test_bucketize_basic(self, params, ie_device, precision, ir_version, temp_dir,
                              use_new_frontend, use_old_api):
-        self._test(*self.create_bucketize_net(**params, ir_version=ir_version,
-                                              use_new_frontend=use_new_frontend),
+        self._test(*self.create_bucketize_net(**params),
                    ie_device, precision, ir_version, temp_dir=temp_dir,
                    use_new_frontend=use_new_frontend, use_old_api=use_old_api)