diff --git a/docs/detection/utils.md b/docs/detection/utils.md
index 9a23fcb4..7b221231 100644
--- a/docs/detection/utils.md
+++ b/docs/detection/utils.md
@@ -25,3 +25,12 @@
 ## filter_polygons_by_area
 
 :::supervision.detection.utils.filter_polygons_by_area
+
+## move_boxes
+
+:::supervision.detection.utils.move_boxes
+
+## scale_boxes
+
+:::supervision.detection.utils.scale_boxes
+
diff --git a/supervision/detection/utils.py b/supervision/detection/utils.py
index 1e5fdc35..33f49131 100644
--- a/supervision/detection/utils.py
+++ b/supervision/detection/utils.py
@@ -383,7 +383,7 @@ def process_roboflow_result(
 
 def move_boxes(xyxy: np.ndarray, offset: np.ndarray) -> np.ndarray:
     """
-    Args:
+    Parameters:
         xyxy (np.ndarray): An array of shape `(n, 4)` containing the bounding boxes
             coordinates in format `[x1, y1, x2, y2]`
         offset (np.array): An array of shape `(2,)` containing offset values in format
@@ -395,6 +395,25 @@ def move_boxes(xyxy: np.ndarray, offset: np.ndarray) -> np.ndarray:
     return xyxy + np.hstack([offset, offset])
 
 
+def scale_boxes(xyxy: np.ndarray, factor: float) -> np.ndarray:
+    """
+    Scale the dimensions of bounding boxes.
+
+    Parameters:
+        xyxy (np.ndarray): An array of shape `(n, 4)` containing the bounding boxes
+            coordinates in format `[x1, y1, x2, y2]`
+        factor (float): A float value representing the factor by which the box
+            dimensions are scaled. A factor greater than 1 enlarges the boxes, while a
+            factor less than 1 shrinks them.
+
+    Returns:
+        (np.ndarray) scaled bounding boxes
+    """
+    centers = (xyxy[:, :2] + xyxy[:, 2:]) / 2
+    new_sizes = (xyxy[:, 2:] - xyxy[:, :2]) * factor
+    return np.concatenate((centers - new_sizes / 2, centers + new_sizes / 2), axis=1)
+
+
 def calculate_masks_centroids(masks: np.ndarray) -> np.ndarray:
     """
     Calculate the centroids of binary masks in a tensor.
diff --git a/test/detection/test_utils.py b/test/detection/test_utils.py
index dc8e9e16..66c84ae6 100644
--- a/test/detection/test_utils.py
+++ b/test/detection/test_utils.py
@@ -10,7 +10,7 @@ from supervision.detection.utils import (
     filter_polygons_by_area,
     move_boxes,
     non_max_suppression,
-    process_roboflow_result,
+    process_roboflow_result, scale_boxes,
 )
 
 TEST_MASK = np.zeros((1, 1000, 1000), dtype=bool)
@@ -504,6 +504,53 @@ def test_move_boxes(
         assert np.array_equal(result, expected_result)
 
 
+@pytest.mark.parametrize(
+    "xyxy, factor, expected_result, exception",
+    [
+        (
+            np.empty(shape=(0, 4)),
+            2.0,
+            np.empty(shape=(0, 4)),
+            DoesNotRaise(),
+        ),  # empty xyxy array
+        (
+            np.array([[0, 0, 10, 10]]),
+            1.0,
+            np.array([[0, 0, 10, 10]]),
+            DoesNotRaise(),
+        ),  # single box with factor equal to 1.0
+        (
+            np.array([[0, 0, 10, 10]]),
+            2.0,
+            np.array([[-5, -5, 15, 15]]),
+            DoesNotRaise(),
+        ),  # single box with factor equal to 2.0
+        (
+            np.array([[0, 0, 10, 10]]),
+            0.5,
+            np.array([[2.5, 2.5, 7.5, 7.5]]),
+            DoesNotRaise(),
+        ),  # single box with factor equal to 0.5
+        (
+            np.array([[0, 0, 10, 10], [10, 10, 30, 30]]),
+            2.0,
+            np.array([[-5, -5, 15, 15], [0, 0, 40, 40]]),
+            DoesNotRaise(),
+        ),  # two boxes with factor equal to 2.0
+    ]
+)
+def test_scale_boxes(
+    xyxy: np.ndarray,
+    factor: float,
+    expected_result: np.ndarray,
+    exception: Exception,
+) -> None:
+    with exception:
+        result = scale_boxes(xyxy=xyxy, factor=factor)
+        assert np.array_equal(result, expected_result)
+
+
+
 @pytest.mark.parametrize(
     "masks, expected_result, exception",
     [