Fuzzy logic is a powerful tool for real-world problems in which data is approximate but not fixed. Fuzzy models are capable of recognizing, representing, manipulating, understanding, and exploiting ambiguous and uncertain facts and information. The healthcare sector plays a very important role in our everyday lives, consisting of a high level of ambiguity in terms of our health and sickness. Disease diagnosis is the result of clinical reasoning based on the investigation of obtained data in medicine. Handling uncertainty and inaccuracies in the diagnosis process of disease is critical since it can aid healthcare workers in disease control. The fuzzy logic technique was considered the most suitable method to represent the uncertainty in diagnosis due to the absence of extensive knowledge, as well as a shortage of time and the fuzzy nature of disease diagnosis. This chapter includes various approaches proposed by the authors in the diagnosis process of various diseases like kidney disease, lung cancer, breast cancer, prostate cancer, etc.