Resource management and optimal allocation are key concepts in many fields. The main goal of this process is to optimize the use of limited resources in order to achieve the best possible results. One of the major challenges in this field is managing the uncertainties and complexities that exist in many real systems. Especially when the available information is not accurate or is incompletely available. Fuzzy models have been proposed as a powerful tool to solve problems related to uncertainties and complexities in optimal resource allocation. These models provide the possibility of managing uncertain and uncertain data. Accordingly, the present study was conducted with the aim of investigating resource management and optimal allocation using fuzzy models. This study is applied in terms of nature and purpose and is a review in terms of research method, and its information was collected through reviewing articles, books, magazines, publications, theses, and indexes written in this field. The results of this research showed that fuzzy models, with their unique capabilities in dealing with uncertainties and incomplete data, have been able to be significantly effective in solving resource allocation problems and optimizing processes. By providing a method for working with uncertain data and analyzing ambiguous situations, these models allow managers to make more optimal decisions in real-world situations. Especially in problems where multiple and diverse variables are involved in resource allocation, fuzzy models can provide more comprehensive solutions while maintaining flexibility.