diff --git a/LeetCode/0973_ K_Closest_Points_to_Origin.py b/LeetCode/0973_ K_Closest_Points_to_Origin.py
new file mode 100644
index 0000000..445b56f
--- /dev/null
+++ b/LeetCode/0973_ K_Closest_Points_to_Origin.py	
@@ -0,0 +1,28 @@
+from heapq import heappop, heappush
+from typing import List, Tuple
+
+
+class Solution:
+    def closest_points(self, points: List[Tuple[float, float]], k: int) -> List[Tuple[float, float]]:
+        """
+        Finds the K points closest to the origin.
+
+        The implementation pushes the points on a Heap with their key being the distance to the origin, then removes K elements from the heap.
+        I chose to go with a more verbose implementation to show how it can be done, but alternatively one could do:
+
+        >>> from heapq import nsmallest
+        ... nsmallest(k, points, key=self.distance)
+        """
+        
+        heap = []
+        for point in points:
+            heappush(heap, (self.distance(point), point))
+
+        return [heappop(heap)[1] for _ in range(k)]
+
+    def distance(self, point: Tuple[float, float]) -> float:
+        """
+        Pythagorean formula to get the distance to the origin.
+        """
+        
+        return (point[0] ** 2 + point[1] ** 2) ** 0.5