diff --git a/Graphs/BidirectionalSearch.js b/Graphs/BidirectionalSearch.js
new file mode 100644
index 0000000000..7c5691790a
--- /dev/null
+++ b/Graphs/BidirectionalSearch.js
@@ -0,0 +1,68 @@
+/*
+Bidirectional search is a graph search algorithm that finds a shortest path from an initial vertex to a goal vertex in a directed graph. 
+It runs two simultaneous searches: one forward from the initial state, and one backward from the goal, stopping when the two meet. 
+The reason for this approach is that in many cases it is faster: for instance, in a simplified model of search problem complexity in which both searches expand a tree with branching factor b, and the distance from start to goal is d, each of the two searches has complexity O(b^(d/2)), 
+and the sum of these two search times is much less than the O(b^d) complexity that would result from a single search from the beginning to the goal.
+
+Reference:
+https://en.wikipedia.org/wiki/Bidirectional_search
+*/
+
+
+class BidirectionalSearch {
+    constructor() {
+      this.adjList = new Map();
+    }
+  
+    addVertex(vertex) {
+      if (!this.adjList.has(vertex)) {
+        this.adjList.set(vertex, []);
+      }
+    }
+  
+    addEdge(vertex1, vertex2) {
+      this.adjList.get(vertex1).push(vertex2);
+      this.adjList.get(vertex2).push(vertex1);
+    }
+  
+    bidirectionalSearch(startVertex, endVertex) {
+      if (!this.adjList.has(startVertex) || !this.adjList.has(endVertex)) {
+        return null; // One of the vertices is not in the graph
+      }
+  
+      const visitedStart = new Set();
+      const visitedEnd = new Set();
+      const queueStart = [startVertex];
+      const queueEnd = [endVertex];
+  
+      visitedStart.add(startVertex);
+      visitedEnd.add(endVertex);
+  
+      while (queueStart.length > 0 && queueEnd.length > 0) {
+        const currentStart = queueStart.shift();
+        const currentEnd = queueEnd.shift();
+  
+        if (visitedEnd.has(currentStart) || visitedStart.has(currentEnd)) {
+          return true; // There is a path between the two vertices
+        }
+  
+        for (const neighbor of this.adjList.get(currentStart) || []) {
+          if (!visitedStart.has(neighbor)) {
+            visitedStart.add(neighbor);
+            queueStart.push(neighbor);
+          }
+        }
+  
+        for (const neighbor of this.adjList.get(currentEnd) || []) {
+          if (!visitedEnd.has(neighbor)) {
+            visitedEnd.add(neighbor);
+            queueEnd.push(neighbor);
+          }
+        }
+      }
+  
+      return false; // No path found between the two vertices
+    }
+  }
+  
+  module.exports = BidirectionalSearch;
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diff --git a/Graphs/test/BidirectionalSearch.test.js b/Graphs/test/BidirectionalSearch.test.js
new file mode 100644
index 0000000000..62a25d407b
--- /dev/null
+++ b/Graphs/test/BidirectionalSearch.test.js
@@ -0,0 +1,30 @@
+import BidirectionalSearch from "../BidirectionalSearch";
+
+describe('Bidirectional Search', () => {
+  it('should find a path between two connected vertices', () => {
+    const graph = new BidirectionalSearch();
+    graph.addVertex('A');
+    graph.addVertex('B');
+    graph.addEdge('A', 'B');
+
+    expect(graph.bidirectionalSearch('A', 'B')).toBe(true);
+  });
+
+  it('should not find a path between two unconnected vertices', () => {
+    const graph = new BidirectionalSearch();
+    graph.addVertex('A');
+    graph.addVertex('B');
+    graph.addVertex('C');
+    graph.addEdge('A', 'B');
+
+    expect(graph.bidirectionalSearch('A', 'C')).toBe(false);
+  });
+
+  it('should handle missing vertices gracefully', () => {
+    const graph = new BidirectionalSearch();
+    graph.addVertex('A');
+    graph.addVertex('B');
+
+    expect(graph.bidirectionalSearch('A', 'C')).toBe(null);
+  });
+});
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