diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index 4d065bd234e0b..20e666bbc7bdb 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -673,7 +673,7 @@ def from_codes(cls, codes, categories=None, ordered=None, dtype=None):
             raise ValueError(msg)
 
         codes = np.asarray(codes)  # #21767
-        if not is_integer_dtype(codes):
+        if len(codes) and not is_integer_dtype(codes):
             msg = "codes need to be array-like integers"
             if is_float_dtype(codes):
                 icodes = codes.astype("i8")
diff --git a/pandas/tests/arrays/categorical/test_constructors.py b/pandas/tests/arrays/categorical/test_constructors.py
index 237ec17f56974..6eb26d26e14bd 100644
--- a/pandas/tests/arrays/categorical/test_constructors.py
+++ b/pandas/tests/arrays/categorical/test_constructors.py
@@ -526,6 +526,9 @@ def test_from_codes_with_float(self):
         codes = [1.0, 2.0, 0]  # integer, but in float dtype
         dtype = CategoricalDtype(categories=["a", "b", "c"])
 
+        # empty codes should not raise for floats
+        Categorical.from_codes([], dtype.categories)
+
         with tm.assert_produces_warning(FutureWarning):
             cat = Categorical.from_codes(codes, dtype.categories)
         tm.assert_numpy_array_equal(cat.codes, np.array([1, 2, 0], dtype="i1"))