diff --git a/tests/test_wer.py b/tests/test_wer.py
index 6017bc4..337b85f 100644
--- a/tests/test_wer.py
+++ b/tests/test_wer.py
@@ -107,6 +107,19 @@ def test_wer_example_4(self):
 
         self.assertEqual(wer(ref, hyp), expected_result)
 
+    def test_wer_empty_strings(self):
+        """
+        Test the wer function with empty reference and hypothesis strings.
+
+        This test evaluates the WER function with empty strings as input.
+        It verifies that the calculated WER is 0 for identical empty strings.
+        """
+        ref = [""]
+        hyp = [""]
+        expected_result = 0.0
+
+        self.assertEqual(wer(ref, hyp), expected_result)
+
 
 if __name__ == "__main__":  # pragma: no cover
     unittest.main()
diff --git a/werpy/metrics.pyx b/werpy/metrics.pyx
index 3d06daf..7198204 100644
--- a/werpy/metrics.pyx
+++ b/werpy/metrics.pyx
@@ -50,7 +50,7 @@ cpdef np.ndarray calculations(object reference, object hypothesis):
                 )
 
     ld = ldm[m][n]
-    wer = ld / m
+    wer = ld / max(m, 1) # Avoid division by 0
 
     insertions, deletions, substitutions = 0, 0, 0
     inserted_words, deleted_words, substituted_words = [], [], []
diff --git a/werpy/wer.py b/werpy/wer.py
index 4b873ab..d283a94 100644
--- a/werpy/wer.py
+++ b/werpy/wer.py
@@ -56,8 +56,9 @@ def wer(reference, hypothesis) -> float:
         transform_word_error_rate_breakdown = np.transpose(
             word_error_rate_breakdown.tolist()
         )
-        wer_result = (np.sum(transform_word_error_rate_breakdown[1])) / (
-            np.sum(transform_word_error_rate_breakdown[2])
+        total_words = np.sum(transform_word_error_rate_breakdown[2])
+        wer_result = np.sum(transform_word_error_rate_breakdown[1]) / max(
+            total_words, 1
         )
     else:
         wer_result = word_error_rate_breakdown[0]