This study proposes a comprehensive uncertainty quantification framework that jointly evaluates data, model, and prediction uncertainties in deep learning-based mineral prospectivity mapping. By modelling and visualizing both data and model uncertainties, the framework transforms deep learning-based mineral prospectivity mapping from deterministic prediction to probabilistic decision-making, thereby enabling more reliable and trustworthy mineral exploration.