diff --git a/src/main/java/com/thealgorithms/backtracking/AStarSearch.java b/src/main/java/com/thealgorithms/backtracking/AStarSearch.java
new file mode 100644
index 000000000000..9223e50be750
--- /dev/null
+++ b/src/main/java/com/thealgorithms/backtracking/AStarSearch.java
@@ -0,0 +1,123 @@
+package com.thealgorithms.backtracking;
+
+// Author: Jivan Jamdar
+
+/* A* Search
+ Problem :  finds the shortest path between nodes in a weighted graph by combining actual travel costs and heuristic estimates. 
+
+ Graph Structure:
+
+ (0) --1.0--> (1) --1.0--> (2) --1.0--> (3) --1.0--> (4) --1.0--> (5)
+ Coordinates:
+
+ Node 0: (0, 0)
+ Node 1: (1, 1)
+ Node 2: (2, 2)
+ Node 3: (3, 3)
+ Node 4: (4, 4)
+ Node 5: (5, 5)
+
+finds the shortest path from Node 0 to Node 5 using the Euclidean distance as a heuristic.
+
+Path Found:
+[0, 1, 2, 3, 4, 5]
+
+*/
+
+import java.util.ArrayList;      
+import java.util.HashMap;      
+import java.util.List;          
+import java.util.Map;
+import java.util.PriorityQueue; 
+import java.util.Comparator;     
+import java.util.Collections;     
+
+public class AStarSearch {
+
+    // Helper class to represent graph edges
+    static class Edge {
+        int target;   // Target vertex
+        double weight; // Weight of the edge
+
+        Edge(int target, double weight) {
+            this.target = target;
+            this.weight = weight;
+        }
+    }
+
+    // Helper class to represent a node with its fScore for the priority queue
+    static class Node {
+        int vertex;  // Vertex index
+        double fScore; // Total estimated cost
+
+        Node(int vertex, double fScore) {
+            this.vertex = vertex;
+            this.fScore = fScore;
+        }
+    }
+
+    // Comparator for priority queue to prioritize based on fScore
+    static class NodeComparator implements Comparator<Node> {
+        public int compare(Node n1, Node n2) {
+            return Double.compare(n1.fScore, n2.fScore);
+        }
+    }
+
+    // Heuristic function (Euclidean distance between two points as an example)
+    public double heuristic(int[] point1, int[] point2) {
+        return Math.sqrt(Math.pow(point1[0] - point2[0], 2) + Math.pow(point1[1] - point2[1], 2));
+    }
+
+    // A* Search algorithm
+    public List<Integer> aStar(List<List<Edge>> graph, int[] start, int[] goal, Map<Integer, int[]> coordinates) {
+        int V = graph.size();
+        double[] gScore = new double[V]; 
+        Arrays.fill(gScore, Double.MAX_VALUE);
+        gScore[start[0]] = 0;
+
+        double[] fScore = new double[V]; // (g + heuristic)
+        Arrays.fill(fScore, Double.MAX_VALUE);
+        fScore[start[0]] = heuristic(coordinates.get(start[0]), coordinates.get(goal[0]));
+
+        PriorityQueue<Node> openSet = new PriorityQueue<>(new NodeComparator());
+        openSet.add(new Node(start[0], fScore[start[0]]));
+
+        Map<Integer, Integer> cameFrom = new HashMap<>(); 
+
+        while (!openSet.isEmpty()) {
+            Node current = openSet.poll();
+
+            // Check if the goal has been reached
+            if (current.vertex == goal[0]) {
+                return reconstructPath(cameFrom, current.vertex);
+            }
+
+            // Explore neighbors
+            for (Edge neighbor : graph.get(current.vertex)) {
+                double tentative_gScore = gScore[current.vertex] + neighbor.weight;
+
+                // If the new path is better, update the scores
+                if (tentative_gScore < gScore[neighbor.target]) {
+                    cameFrom.put(neighbor.target, current.vertex);
+                    gScore[neighbor.target] = tentative_gScore;
+                    fScore[neighbor.target] = gScore[neighbor.target] + heuristic(coordinates.get(neighbor.target), coordinates.get(goal[0]));
+                    openSet.add(new Node(neighbor.target, fScore[neighbor.target]));
+                }
+            }
+        }
+
+        return Collections.emptyList(); 
+    }
+
+    // Helper method to reconstruct the path from start to goal
+    private List<Integer> reconstructPath(Map<Integer, Integer> cameFrom, int current) {
+        List<Integer> path = new ArrayList<>();
+        path.add(current);
+        while (cameFrom.containsKey(current)) {
+            current = cameFrom.get(current);
+            path.add(current);
+        }
+        Collections.reverse(path);
+        return path;
+    }
+}
diff --git a/src/test/java/com/thealgorithms/backtracking/AStarSearchTest.java b/src/test/java/com/thealgorithms/backtracking/AStarSearchTest.java
new file mode 100644
index 000000000000..5876d42d2117
--- /dev/null
+++ b/src/test/java/com/thealgorithms/backtracking/AStarSearchTest.java
@@ -0,0 +1,39 @@
+package com.thealgorithms.backtracking;
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import org.junit.jupiter.api.Test;
+
+public class AStarSearchTest {
+
+    @Test
+    void testSimpleAStar() {
+        AStarSearch aStar = new AStarSearch();
+
+        List<List<AStarSearch.Edge>> graph = new ArrayList<>();
+        for (int i = 0; i < 6; i++) {
+            graph.add(new ArrayList<>());
+        }
+
+        graph.get(0).add(new AStarSearch.Edge(1, 1.0)); 
+        graph.get(1).add(new AStarSearch.Edge(2, 1.0)); 
+        graph.get(2).add(new AStarSearch.Edge(3, 1.0)); 
+        graph.get(3).add(new AStarSearch.Edge(4, 1.0)); 
+        graph.get(4).add(new AStarSearch.Edge(5, 1.0));
+
+        Map<Integer, int[]> coordinates = new HashMap<>();
+        coordinates.put(0, new int[]{0, 0});
+        coordinates.put(1, new int[]{1, 1});
+        coordinates.put(2, new int[]{2, 2});
+        coordinates.put(3, new int[]{3, 3});
+        coordinates.put(4, new int[]{4, 4});
+        coordinates.put(5, new int[]{5, 5});
+
+        List<Integer> path = aStar.aStar(graph, new int[]{0, 0}, new int[]{5, 5}, coordinates);
+        
+        assertEquals(Arrays.asList(0, 1, 2, 3, 4, 5), path);
+    }
+}