Since the inception of the digital world, computers have been able to comprehend the binary values of either ‘0’ or ‘1’. Performing huge arrays of complex calculations on the basis of the binary values was an essential development but in practical and tangible situations, this is not always the case. The limitations faced by a computer when classifying many ambiguous questions like whether the temperature of water is warm enough or whether a person is beautiful or not etc. lead to the birth of the concept of ‘fuzzy logic’, an approach proposed to give high accuracy in a predictive system. Such fuzzy logic approach imitates how the human brain analyses and resolves issues. In contrast to the conventional Boolean approach to logic, fuzzy logic allows computers to respond to varying degrees of truth. The goal of fuzzy logic is to simulate human decision-making by employing natural language words rather than strictly mathematical ones. Fuzzy logic has applications in cutting-edge research, technology, and commercial domains. Engineers (electrical, mechanical, civil, chemical, aerospace, agricultural, biomedical, computer, environmental, geological, industrial, and mechatronics), mathematicians, computer software developers and researchers, natural scientists (biology, chemistry, earth science, and physics), medical researchers, and social scientists (economics, management, political science, and psychoanalysis) all find fuzzy logic to be of great use in research and development. In this chapter, we look into the internal mechanics, limitations and the various applications of fuzzy logic.