Aiming at the problem of short effective prediction time for the movement history of amphibious aircraft in waves, this paper proposes to predict the statistical values of amphibious aircraft movement over a period of time, and constructs a prediction model for the statistical characteristics of amphibious aircraft movement based on long short-term memory neural networks. Taking the NACA TN 2929 amphibious aircraft as an example, based on its numerical simulation data, the statistical values of the three degrees of freedom motion of heave, roll, and pitch of amphibious aircraft under sea conditions of level 3, 4, and 5 were predicted, and their prediction effects were analyzed in detail. The results show that the LSTM neural network-based model for predicting the statistical characteristics of amphibious aircraft motion has good prediction accuracy. In practical engineering applications, this model can accurately predict the statistical values of amphibious aircraft motion in the future, providing auxiliary decision-making information for offshore operations.