During the execution of practical tasks, the motion trajectory of underwater gliders exhibits significant uncertainty and nonlinearity due to the influence of the complex marine environment. These factors present major challenges for accurate trajectory prediction. To address this issue, this paper proposes a trajectory prediction method for underwater gliders based on dynamic intelligent simulation. Trajectory data are first collected from dynamic simulations of underwater glider navigation, serving as the foundation for the research. After preprocessing the original data, the TimesNet model is employed for training and prediction. The prediction performance is then evaluated through comparative experiments and analyses. Experimental results indicate that the proposed method achieves superior performance in both prediction accuracy and reliability, confirming its practical effectiveness for underwater glider trajectory forecasting. Furthermore, this approach provides a novel perspective for trajectory prediction in other complex dynamic systems.