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Multi-Agent Trajectory Prediction is a critical and challenging component across different safety–critical engineering applications, e.g., autonomous driving and flight systems. Trajectory prediction tools are required for the next-generation air transportation system (NextGen). In practice, the prediction of aircraft trajectories needs to consider the impact of various sources, such as environmental conditions, pilot/controller behaviors, and potential conflicts with nearby aircraft. Huge uncertainties associated with these factors lead to the untrustworthiness of a deterministic trajectory prediction model. Moreover, the safety assurance in the near-terminal area is of specific interest due to the increased airspace complexity, where the instrument/visual flight rules are applied. In this work, we propose the Bayesian Spatio-Temporal grAph tRansformer (B-STAR) architecture to model the spatial and temporal relationship of …