diff --git a/src/main/java/com/thealgorithms/randomized/RandomizedClosestPair.java b/src/main/java/com/thealgorithms/randomized/RandomizedClosestPair.java
new file mode 100644
index 000000000000..92b28be75223
--- /dev/null
+++ b/src/main/java/com/thealgorithms/randomized/RandomizedClosestPair.java
@@ -0,0 +1,108 @@
+package com.thealgorithms.randomized;
+
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.Comparator;
+import java.util.List;
+import java.util.ArrayList;
+import java.util.Random;
+
+/**
+ * Randomized Closest Pair of Points Algorithm
+ *
+ * Use Case:
+ * - Efficiently finds the closest pair of points in a 2D plane.
+ * - Applicable in computational geometry, clustering, and graphics.
+ *
+ * Time Complexity:
+ * - Expected: O(n log n) using randomized divide and conquer
+ *
+ * @see Closest Pair of Points - Wikipedia
+ */
+public final class RandomizedClosestPair {
+
+ // Prevent instantiation of utility class
+ private RandomizedClosestPair() {
+ throw new UnsupportedOperationException("Utility class");
+ }
+
+ public static class Point {
+ public final double x, y;
+ public Point(double x, double y) {
+ this.x = x;
+ this.y = y;
+ }
+ }
+
+ public static double findClosestPairDistance(Point[] points) {
+ List shuffled = new ArrayList<>(Arrays.asList(points));
+ Collections.shuffle(shuffled, new Random());
+
+ Point[] px = shuffled.toArray(new Point[0]);
+ Arrays.sort(px, Comparator.comparingDouble(p -> p.x));
+
+ Point[] py = px.clone();
+ Arrays.sort(py, Comparator.comparingDouble(p -> p.y));
+
+ return closestPair(px, py);
+ }
+
+ private static double closestPair(Point[] px, Point[] py) {
+ int n = px.length;
+ if (n <= 3) {
+ return bruteForce(px);
+ }
+
+ int mid = n / 2;
+ Point midPoint = px[mid];
+
+ Point[] Qx = Arrays.copyOfRange(px, 0, mid);
+ Point[] Rx = Arrays.copyOfRange(px, mid, n);
+
+ List Qy = new ArrayList<>();
+ List Ry = new ArrayList<>();
+ for (Point p : py) {
+ if (p.x <= midPoint.x) Qy.add(p);
+ else Ry.add(p);
+ }
+
+ double d1 = closestPair(Qx, Qy.toArray(new Point[0]));
+ double d2 = closestPair(Rx, Ry.toArray(new Point[0]));
+
+ double d = Math.min(d1, d2);
+
+ List strip = new ArrayList<>();
+ for (Point p : py) {
+ if (Math.abs(p.x - midPoint.x) < d) {
+ strip.add(p);
+ }
+ }
+
+ return Math.min(d, stripClosest(strip, d));
+ }
+
+ private static double bruteForce(Point[] points) {
+ double min = Double.POSITIVE_INFINITY;
+ for (int i = 0; i < points.length; i++) {
+ for (int j = i + 1; j < points.length; j++) {
+ min = Math.min(min, distance(points[i], points[j]));
+ }
+ }
+ return min;
+ }
+
+ private static double stripClosest(List strip, double d) {
+ double min = d;
+ int n = strip.size();
+ for (int i = 0; i < n; i++) {
+ for (int j = i + 1; j < n && (strip.get(j).y - strip.get(i).y) < min; j++) {
+ min = Math.min(min, distance(strip.get(i), strip.get(j)));
+ }
+ }
+ return min;
+ }
+
+ private static double distance(Point p1, Point p2) {
+ return Math.hypot(p1.x - p2.x, p1.y - p2.y);
+ }
+}
diff --git a/src/test/java/com/thealgorithms/randomized/RandomizedClosestPairTest.java b/src/test/java/com/thealgorithms/randomized/RandomizedClosestPairTest.java
new file mode 100644
index 000000000000..5b402f3be90d
--- /dev/null
+++ b/src/test/java/com/thealgorithms/randomized/RandomizedClosestPairTest.java
@@ -0,0 +1,45 @@
+package com.thealgorithms.randomized;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+import com.thealgorithms.randomized.RandomizedClosestPair.Point;
+import org.junit.jupiter.api.Test;
+
+public class RandomizedClosestPairTest {
+
+ @Test
+ public void testClosestPairBasic() {
+ Point[] points = new Point[] {
+ new Point(2, 3),
+ new Point(12, 30),
+ new Point(40, 50),
+ new Point(5, 1),
+ new Point(12, 10),
+ new Point(3, 4)
+ };
+ double result = RandomizedClosestPair.findClosestPairDistance(points);
+ assertEquals(Math.hypot(1, 1), result, 0.01); // Closest pair: (2,3) and (3,4)
+ }
+
+ @Test
+ public void testIdenticalPoints() {
+ Point[] points = new Point[] {
+ new Point(0, 0),
+ new Point(0, 0),
+ new Point(1, 1),
+ };
+ double result = RandomizedClosestPair.findClosestPairDistance(points);
+ assertEquals(0.0, result, 0.00001);
+ }
+
+ @Test
+ public void testMinimalCase() {
+ Point[] points = new Point[] {
+ new Point(0, 0),
+ new Point(3, 4)
+ };
+ double result = RandomizedClosestPair.findClosestPairDistance(points);
+ assertEquals(5.0, result, 0.00001);
+ }
+}
+