Fuzzification is the process of transforming crisp, precise data into fuzzy values that represent degrees of truth. In this context, "fuzzy" refers to the idea that not all information can be categorized as simply true or false; instead, it can exist in varying degrees. This is particularly useful in situations where data is uncertain or imprecise, allowing for more nuanced decision-making. In fuzzy logic systems, fuzzification helps to create a more flexible framework for reasoning. By converting specific inputs into fuzzy sets, such as low, medium, and high, it enables algorithms to handle ambiguity and make better predictions or classifications. This approach is widely used in fields like artificial intelligence and control systems.