founded by Florentin Smarandache in 1995, is considered one of the most significant modern developments in handling ambiguity and uncertainty in data. It is based on three main dimensions: truth (T), indeterminacy (I), and falsity (F). Unlike classical or fuzzy logic, the sum of these values is not restricted to one, which gives neutrosophic logic greater flexibility in addressing complex and contradictory situations. Its importance in scientific research lies in providing a mathematical tool that allows researchers to represent incomplete or inconsistent data more realistically, thus producing more accurate models. For instance, it can be applied in medical research to analyze uncertain test results, in social sciences to model situations involving conflicting opinions and hesitation, as well as in computer science and artificial intelligence to support decision-making in uncertain environments. Therefore, adopting neutrosophic logic in research offers a methodological framework that helps scholars produce deeper and more flexible findings compared to traditional approaches, thereby enhancing the value of both applied and theoretical studies.