Belief Functions are mathematical tools used in the field of Dempster-Shafer theory to represent uncertainty and incomplete information. They allow for the assignment of belief to different hypotheses based on available evidence, distinguishing between what is known, what is uncertain, and what is impossible. In a belief function, a set of possible outcomes is represented, and each outcome is assigned a degree of belief. This degree reflects how strongly the evidence supports that outcome, enabling decision-makers to evaluate risks and make informed choices even when data is limited or ambiguous.