This review paper discusses the theoretical principles, methodologies, and applications of Fuzzy Logic in dealing with ambiguity and uncertainty in real-world situations. It analyzes also the role of this discipline in the field of Artificial Intelligence, Collaborative Learning, and Control Systems, emphasizing its capacity to handle imprecise data and enhance decision-making processes. A systematic literature review was conducted and involved the consultation of academic and scientific databases such as IEEE Xplore, SpringerLink, and Google Scholar, applying criteria of inclusion and exclusion to ensure the relevance and quality of the selected studies. According to the findings, Fuzzy Logic plays an important and central role in Neuro-Fuzzy Systems, where it works in combination with Artificial Neural Networks to solve engineering problems and in Collaborative Learning environments, where it personalizes the learning experience through uncertainty modeling. The results also show that Fuzzy Logic has the potential for applications as diverse as automation and educational technology, thus confirming its worth in mastering complexity and enhancing systems’ flexibility.