Intelligent supply chain management, which emerged with the integration of digitalized processes into supply chain management, encourages companies to redesign their supply chains to meet customer needs and expectations for improved purchasing and service quality. Most companies try to strike a balance between working capital, operating costs, and optimal service levels. For this reason, it is very important to use the right supply chain tool that provides the most efficiency in supply chain management. In this study, the evaluation of supply chain tools for intelligent supply chain management is considered as a Multi- Criteria Decision Making (MCDM) problem. However, it becomes difficult for experts to evaluate and make decisions about the system when the information is insufficient and uncertain. Therefore, in this study, the fuzzy approach is used to evaluate the MCDM problem more realistically and flexibly. The aim of the study is to propose an evaluation model and integrated analytic methods for the evaluation of supply chain tools for the intelligent supply chain management. The fuzzy Analytic Hierarchy Process (AHP) method is used to calculate the weights of the criteria and fuzzy COmplex PRoportional ASsessment (COPRAS) is used to rank the supply chain tools. Finally, an application is offered to demonstrate the proposed methodology's possible use. This paper guides researchers and practitioners with an evaluation methodology based on fuzziness for intelligent supply chain management.