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In this paper, a multi-stage path prediction algorithm of the decentralized mission planning for cooperative UAVs is presented. The planning horizon is defined as the period between the start of task assignment and completion of any task. In every planning horizon, each UAV utilizes the A* algorithm to predict the paths to all tasks and provide the path distances for task assignment. Furthermore, the cluster algorithm is introduced to modify the tasks value vector. The UAVs negotiate the task assignment solution and calculate the shortest path to assigned task in the detection range in real time. Finally, the B-spline curve is addressed to convert the shortest path into flyable smoothing trajectory that subject to the flight constraints. For validation, the scenario of multiple UAVs to perform cooperative missions is considered. Numerical results show that the proposed algorithm can achieve the quasi-optimal assignment solution and generate the flyable trajectory in real time. In addition, the satisfactory performance to accomplish the pop-up tasks is demonstrated.