diff --git a/Graphs/AStar.js b/Graphs/AStar.js
new file mode 100644
index 0000000000..3f93625573
--- /dev/null
+++ b/Graphs/AStar.js
@@ -0,0 +1,78 @@
+/**
+ * A* Search Algorithm
+ *
+ * Finds the shortest path between a start node and a target node in a
+ * weighted graph, using a heuristic function to guide the search toward
+ * the target, generally exploring fewer nodes than an uninformed search
+ * such as Dijkstra's algorithm.
+ *
+ * The algorithm is only guaranteed to find the true shortest path if the
+ * heuristic is admissible, i.e. it never overestimates the real cost from
+ * a node to the target. Passing a heuristic that always returns 0 makes
+ * A* behave exactly like Dijkstra's algorithm.
+ *
+ * For more info: https://en.wikipedia.org/wiki/A*_search_algorithm
+ *
+ * @param {Object<string, Array<[string, number]>>} graph - Adjacency list mapping each node to an array of [neighbor, weight] pairs.
+ * @param {string} start - The node to start the search from.
+ * @param {string} target - The node to search for.
+ * @param {(node: string) => number} heuristic - Estimated cost from a node to the target.
+ * @returns {{ path: string[], cost: number } | null} The shortest path from start to target and its total cost, or null if no path exists.
+ *
+ * @example
+ * const graph = {
+ *   A: [['B', 1], ['C', 4]],
+ *   B: [['C', 1], ['D', 5]],
+ *   C: [['D', 1]],
+ *   D: []
+ * }
+ * const heuristic = (node) => ({ A: 2, B: 2, C: 1, D: 0 })[node]
+ *
+ * aStarSearch(graph, 'A', 'D', heuristic)
+ * // => { path: ['A', 'B', 'C', 'D'], cost: 3 }
+ */
+
+import { KeyPriorityQueue } from '../Data-Structures/Heap/KeyPriorityQueue.js'
+
+const reconstructPath = (cameFrom, current) => {
+  const path = [current]
+  while (cameFrom.has(current)) {
+    current = cameFrom.get(current)
+    path.unshift(current)
+  }
+  return path
+}
+
+function aStarSearch(graph, start, target, heuristic) {
+  const gScore = new Map([[start, 0]])
+  const cameFrom = new Map()
+
+  const openSet = new KeyPriorityQueue()
+  openSet.push(start, heuristic(start))
+
+  while (!openSet.isEmpty()) {
+    const current = openSet.pop()
+
+    if (current === target) {
+      return {
+        path: reconstructPath(cameFrom, current),
+        cost: gScore.get(current)
+      }
+    }
+
+    const neighbors = graph[current] || []
+    for (const [neighbor, weight] of neighbors) {
+      const tentativeGScore = gScore.get(current) + weight
+
+      if (tentativeGScore < (gScore.get(neighbor) ?? Infinity)) {
+        cameFrom.set(neighbor, current)
+        gScore.set(neighbor, tentativeGScore)
+        openSet.update(neighbor, tentativeGScore + heuristic(neighbor))
+      }
+    }
+  }
+
+  return null
+}
+
+export { aStarSearch }
diff --git a/Graphs/test/AStar.test.js b/Graphs/test/AStar.test.js
new file mode 100644
index 0000000000..c2b207d2cc
--- /dev/null
+++ b/Graphs/test/AStar.test.js
@@ -0,0 +1,67 @@
+import { aStarSearch } from '../AStar.js'
+
+const graph = {
+  A: [
+    ['B', 1],
+    ['C', 4]
+  ],
+  B: [
+    ['C', 1],
+    ['D', 5]
+  ],
+  C: [['D', 1]],
+  D: []
+}
+
+const heuristics = { A: 2, B: 2, C: 1, D: 0 }
+const heuristic = (node) => heuristics[node]
+const zeroHeuristic = () => 0
+
+test('Finds the shortest path using an admissible heuristic', () => {
+  expect(aStarSearch(graph, 'A', 'D', heuristic)).toEqual({
+    path: ['A', 'B', 'C', 'D'],
+    cost: 3
+  })
+})
+
+test('Matches Dijkstra (zero heuristic) on the same graph', () => {
+  expect(aStarSearch(graph, 'A', 'D', zeroHeuristic)).toEqual({
+    path: ['A', 'B', 'C', 'D'],
+    cost: 3
+  })
+})
+
+test('Returns a path with cost 0 when start equals target', () => {
+  expect(aStarSearch(graph, 'A', 'A', heuristic)).toEqual({
+    path: ['A'],
+    cost: 0
+  })
+})
+
+test('Returns null when no path exists', () => {
+  const disconnectedGraph = { A: [['B', 1]], B: [], C: [] }
+  expect(aStarSearch(disconnectedGraph, 'A', 'C', zeroHeuristic)).toBeNull()
+})
+
+test('Finds the shortest path in a larger graph with multiple routes', () => {
+  const largerGraph = {
+    A: [
+      ['B', 2],
+      ['C', 5]
+    ],
+    B: [
+      ['D', 4],
+      ['E', 2]
+    ],
+    C: [['E', 1]],
+    D: [['F', 1]],
+    E: [['F', 4]],
+    F: []
+  }
+  const largerHeuristic = () => 0
+
+  expect(aStarSearch(largerGraph, 'A', 'F', largerHeuristic)).toEqual({
+    path: ['A', 'B', 'D', 'F'],
+    cost: 7
+  })
+})