Path forecasting for air strike aircraft is one of the assistant methods in assessing the schemes of the deployment of air defense forces. A model of path forecasting is built based on analyzing the path forecasting problem for air strike aircraft. Then a path forecasting algorithm by evolving waypoints is presented. The methods of path forecasting by using traditional evolutionary algorithms (EAs) can hardly exploit the high quality waypoints in previous candidate paths for further evolution, since they regard all the waypoints of a path as an integrated individual. The proposed algorithm improves the framework of the traditional EAs and evaluation functions to evaluate and evolve waypoints separately. The waypoints are evolved with JADE, a state-of-the-art variant of the differential evolution (DE) algorithm, and evaluated and selected by using a multi-criteria handling method based on the priorities, exploiting high quality waypoints. To test the capabilities of the new algorithm, 4 scenarios with 15, 30, 60 and 120 obstacles are constructed respectively. The simulation results show that the proposed algorithm meets the needs for the path forecasting for air strike aircraft effectively, and its performance is previous to the genetic algorithm-based path forecasting algorithm in the scenarios with lots of obstacles.