diff --git a/8puzzleAstar.py b/8puzzleAstar.py
new file mode 100644
index 0000000..805a94b
--- /dev/null
+++ b/8puzzleAstar.py
@@ -0,0 +1,77 @@
+import copy
+import heapq
+
+class Puzzle:
+    
+    def __init__(self, initial_state):
+        self.goal_state = [[1, 2, 3], [4, 5, 6], [7, 8, 0]]
+        self.initial_state = initial_state
+        self.open_list = []
+        self.closed_list = []
+    
+    def get_heuristic(self, state):
+        heuristic = 0
+        for i in range(3):
+            for j in range(3):
+                if state[i][j] != 0:
+                    x_goal, y_goal = divmod(state[i][j] - 1, 3)
+                    heuristic += abs(i - x_goal) + abs(j - y_goal)
+        return heuristic
+    
+    def get_blank_position(self, state):
+        for i in range(3):
+            for j in range(3):
+                if state[i][j] == 0:
+                    return (i, j)
+    
+    def get_successors(self, state):
+        successors = []
+        i_blank, j_blank = self.get_blank_position(state)
+        for x, y in [(0, 1), (1, 0), (0, -1), (-1, 0)]:
+            if 0 <= i_blank + x < 3 and 0 <= j_blank + y < 3:
+                new_state = copy.deepcopy(state)
+                new_state[i_blank][j_blank], new_state[i_blank + x][j_blank + y] = new_state[i_blank + x][j_blank + y], new_state[i_blank][j_blank]
+                successors.append(new_state)
+        return successors
+    
+    def solve(self):
+        start_node = (self.get_heuristic(self.initial_state), self.initial_state, 0, None)
+        heapq.heappush(self.open_list, start_node)
+        
+        while self.open_list:
+            current_node = heapq.heappop(self.open_list)
+            current_cost = current_node[2]
+            current_state = current_node[1]
+            
+            if current_state == self.goal_state:
+                path = []
+                while current_node:
+                    path.append(current_node[1])
+                    current_node = current_node[3]
+                return reversed(path)
+            
+            self.closed_list.append(current_state)
+            successors = self.get_successors(current_state)
+            for successor in successors:
+                if successor not in self.closed_list:
+                    g_cost = current_cost + 1
+                    h_cost = self.get_heuristic(successor)
+                    f_cost = g_cost + h_cost
+                    new_node = (f_cost, successor, g_cost, current_node)
+                    heapq.heappush(self.open_list, new_node)
+        
+        return None
+
+# Run the Solver
+initial_state = [[1,2, 3], [4,5,6], [0,7,8]]
+solver = Puzzle(initial_state)
+solution = solver.solve()
+
+if solution:
+    for idx, state in enumerate(solution):
+        print(f"Move {idx + 1}:")
+        for row in state:
+            print(row)
+        print()
+else:
+    print("No solution found.")
diff --git a/Python/8puzzleBSF.py b/Python/8puzzleBSF.py
new file mode 100644
index 0000000..fcf8477
--- /dev/null
+++ b/Python/8puzzleBSF.py
@@ -0,0 +1,75 @@
+from collections import deque
+
+def is_goal(state):
+    return state == [[1, 2, 3], [4, 5, 6], [7, 8, 0]]
+
+def find_moves(state):
+    moves = []
+    zero_row, zero_col = find_zero(state)
+    if zero_row > 0:
+        moves.append("up")
+    if zero_row < 2:
+        moves.append("down")
+    if zero_col > 0:
+        moves.append("left")
+    if zero_col < 2:
+        moves.append("right")
+    return moves
+
+def find_zero(state):
+    for i in range(3):
+        for j in range(3):
+            if state[i][j] == 0:
+                return i, j
+
+def perform_move(state, move):
+    new_state = [row[:] for row in state]
+    zero_row, zero_col = find_zero(state)
+    if move == "up":
+        new_row, new_col = zero_row - 1, zero_col
+    elif move == "down":
+        new_row, new_col = zero_row + 1, zero_col
+    elif move == "left":
+        new_row, new_col = zero_row, zero_col - 1
+    elif move == "right":
+        new_row, new_col = zero_row, zero_col + 1
+    new_state[zero_row][zero_col], new_state[new_row][new_col] = new_state[new_row][new_col], new_state[zero_row][zero_col]
+    return new_state
+
+def solve_puzzle(initial_state):
+    if is_goal(initial_state):
+        return [initial_state]
+    
+    visited = set()
+    queue = deque([(initial_state, [])])
+
+    while queue:
+        state, path = queue.popleft()
+        visited.add(tuple(map(tuple, state)))
+
+        for move in find_moves(state):
+            new_state = perform_move(state, move)
+            if tuple(map(tuple, new_state)) not in visited:
+                new_path = path + [new_state]
+                if is_goal(new_state):
+                    return new_path
+                queue.append((new_state, new_path))
+
+    return None
+
+# Example usage:
+initial_state = [
+    [1, 2, 3],
+    [4, 5, 0],
+    [7, 8, 6]
+]
+
+solution = solve_puzzle(initial_state)
+if solution:
+    print("Solution found in", len(solution)-1, "moves:")
+    for i, state in enumerate(solution):
+        print("\nMove", i)
+        for row in state:
+            print(row)
+else:
+    print("No solution found.")