diff --git a/docs/source/release_notes.rst b/docs/source/release_notes.rst
index de411e8ce..04eb05119 100644
--- a/docs/source/release_notes.rst
+++ b/docs/source/release_notes.rst
@@ -14,6 +14,7 @@ Future Release
         * Fixed ``IntegerNullable`` inference by checking values are within valid ``Int64`` bounds (:pr:`1572`)
         * Update demo dataset links to point to new endpoint (:pr:`1570`)
         * Fix DivisionByZero error in ``type_system.py`` (:pr:`1571`)
+        * Fix Categorical dtype inference for ``PostalCode`` logical type (:pr:`1574`)
         * Fixed issue where forcing a ``Boolean`` logical type on a column of 0.0s and 1.0s caused incorrect transformation (:pr:`1576`)
     * Changes
         * Unpin dask dependency (:pr:`1561`)
diff --git a/woodwork/tests/type_system/conftest.py b/woodwork/tests/type_system/conftest.py
index 2b48563f8..2059aad34 100644
--- a/woodwork/tests/type_system/conftest.py
+++ b/woodwork/tests/type_system/conftest.py
@@ -282,6 +282,33 @@ def natural_language(request):
     return request.getfixturevalue(request.param)
 
 
+# Postal Inference Fixtures
+@pytest.fixture
+def pandas_postal_codes():
+    return [
+        pd.Series(10 * ["77002", "55106"]),
+        pd.Series(10 * ["77002-0000", "55106-0000"]),
+        pd.Series(10 * ["12345", "12345", "12345-6789", "12345-0000"]),
+    ]
+
+
+@pytest.fixture
+def dask_postal_codes(pandas_postal_codes):
+    return [pd_to_dask(series) for series in pandas_postal_codes]
+
+
+@pytest.fixture
+def spark_postal_codes(pandas_postal_codes):
+    return [pd_to_spark(series) for series in pandas_postal_codes]
+
+
+@pytest.fixture(
+    params=["pandas_postal_codes", "dask_postal_codes", "spark_postal_codes"],
+)
+def postal(request):
+    return request.getfixturevalue(request.param)
+
+
 # Unknown Inference Fixtures
 @pytest.fixture
 def pandas_strings():
@@ -357,7 +384,7 @@ def pyspark_empty_series(pandas_empty_series):
 
 
 @pytest.fixture(
-    params=["pandas_empty_series", "dask_empty_series", "pyspark_empty_series"]
+    params=["pandas_empty_series", "dask_empty_series", "pyspark_empty_series"],
 )
 def empty_series(request):
     return request.getfixturevalue(request.param)
diff --git a/woodwork/tests/type_system/test_ltype_inference.py b/woodwork/tests/type_system/test_ltype_inference.py
index 9a3d41af6..b5c7b461a 100644
--- a/woodwork/tests/type_system/test_ltype_inference.py
+++ b/woodwork/tests/type_system/test_ltype_inference.py
@@ -13,6 +13,7 @@
     IntegerNullable,
     LogicalType,
     NaturalLanguage,
+    PostalCode,
     Timedelta,
     Unknown,
 )
@@ -132,6 +133,16 @@ def test_categorical_inference(categories):
             assert isinstance(inferred_type, Categorical)
 
 
+def test_postal_inference(postal):
+    dtypes = ["category", "string"]
+    for series in postal:
+        if _is_spark_series(series):
+            dtypes = get_spark_dtypes(dtypes)
+        for dtype in dtypes:
+            inferred_dtype = ww.type_system.infer_logical_type(series.astype(dtype))
+            assert isinstance(inferred_dtype, PostalCode)
+
+
 def test_natural_language_inference(natural_language):
     dtypes = ["object", "string"]
     if _is_spark_series(natural_language[0]):
diff --git a/woodwork/type_sys/inference_functions.py b/woodwork/type_sys/inference_functions.py
index f6d1699d5..af543be63 100644
--- a/woodwork/type_sys/inference_functions.py
+++ b/woodwork/type_sys/inference_functions.py
@@ -156,7 +156,10 @@ def __call__(self, series: pd.Series) -> bool:
         regex = self.get_regex()
 
         # Includes a check for object dtypes
-        if not pdtypes.is_string_dtype(series.dtype):
+        if not (
+            pdtypes.is_categorical_dtype(series.dtype)
+            or pdtypes.is_string_dtype(series.dtype)
+        ):
             return False
 
         try: