diff --git a/tests/utils.py b/tests/utils.py
index 28724931..3245adfa 100644
--- a/tests/utils.py
+++ b/tests/utils.py
@@ -1,3 +1,4 @@
+from difflib import SequenceMatcher
 from pathlib import Path
 
 from mindee.mindee_http.mindee_api import (
@@ -27,56 +28,11 @@ def dummy_envvars(monkeypatch) -> None:
 EXTRAS_DIR = Path("./tests/data/extras/")
 
 
-def levenshtein_distance(reference_str: str, target_str: str) -> int:
-    """
-    Calculate the Levenshtein distance between two strings.
-
-    The Levenshtein distance is a measure of the difference between two sequences.
-    Informally, the Levenshtein distance between two words is the minimum number
-    of single-character edits (insertions, deletions or substitutions) required
-    to change one word into the other.
-
-
-    :param reference_str: The reference string.
-    :param target_str: The target string.
-
-    :return: The distance between the two strings.
-    """
-    reference_len, target_len = len(reference_str), len(target_str)
-    previous_row = list(range(target_len + 1))
-    current_row = [0] * (target_len + 1)
-
-    for i in range(reference_len):
-        current_row[0] = i + 1
-
-        for j in range(target_len):
-            deletion_cost = previous_row[j + 1] + 1
-            insertion_cost = current_row[j] + 1
-            substitution_cost = (
-                previous_row[j]
-                if reference_str[i] == target_str[j]
-                else previous_row[j] + 1
-            )
-
-            current_row[j + 1] = min(deletion_cost, insertion_cost, substitution_cost)
-
-        previous_row, current_row = current_row, previous_row
-
-    return previous_row[target_len]
-
-
 def levenshtein_ratio(ref_str: str, target_str: str) -> float:
     """
     Calculates the Levenshtein ratio between two strings.
-
     :param ref_str: Reference string.
     :param target_str: Target String.
     :return: Ratio between the two strings
     """
-    lev_distance = levenshtein_distance(ref_str, target_str)
-    max_len = max(len(ref_str), len(target_str))
-
-    if max_len == 0:
-        return 1.0
-
-    return 1.0 - (lev_distance / max_len)
+    return SequenceMatcher(None, ref_str, target_str).ratio()