The flight trajectory is composed of a large amount of time series data and follows certain motion rules. Predicting the flight trajectory of enemy patrol aircraft can effectively improve the survival rate of fighter jets. This paper proposes a flight trajectory prediction method based on C-GRU, aiming at the low accuracy of flight trajectory prediction by the existing single prediction model. Use flight simulation to obtain multiple sets of flight trajectory coordinate point data for C-GRU network model parameter training to achieve flight trajectory prediction. Through the analysis of simulation results, the average absolute error of multiple sets of prediction data on the X, Y, and Z axes of the C-GRU network model is within 4.5m, and the average time overhead of network model prediction is about 4.1ms; Compared with the smaller trajectory data, the two sets of root mean square errors of the Y and Z axes are similar. At the same time, compared with the GRU and LSTM network models, the error is the smallest, and the predicted results are more accurate when the average time-consuming is close. Therefore, the model proposed in this paper is suitable for different flight trajectories, and the prediction results have high reliability.