A Fuzzy Inference System (FIS) is a computational framework used to model and analyze complex systems that are difficult to describe with precise mathematical equations. It employs fuzzy logic, which allows for reasoning with uncertain or imprecise information. FIS uses a set of rules and membership functions to evaluate inputs and produce outputs, making it useful in various applications like control systems and decision-making. The main components of a FIS include the fuzzification interface, which converts crisp inputs into fuzzy values, the rule base that contains the fuzzy rules, and the defuzzification interface, which translates fuzzy outputs back into crisp values. This system is particularly effective in fields such as artificial intelligence, automated control, and data analysis.