The chapter examines the challenges and opportunities in integrating fuzzy logic with circular economy (CE) practices. The CE model increases relevance in addressing global environmental issues through sustainability, waste reduction, and efficient resource management. Yet there are many challenges, such as uncertainty in the flows of materials, complex demand forecasting, and integrating diversities of stakeholders. Previous researches have looked into the fuzzy logic application to handle uncertainty and imprecision in various systems but are underinvestigated for their application in the circular economy. This chapter fills this gap by investigating how fuzzy logic can enhance decision-making in CE processes, especially in areas like product life cycle management, resource recovery, and supply chain optimization. The research uses a combination of case studies and analytical methods to demonstrate how fuzzy systems can model uncertainty and provide adaptive solutions in dynamic CE environments. The findings show that fuzzy logic offers practical and scalable solutions for overcoming key barriers to CE implementation. The chapter emphasizes fuzzy algorithm refinement and the inclusion of future technologies such as AI and IoT in order to push forward in circular economy strategies for sustainable, efficient, and more resilient systems. © 2026 selection and editorial matter, Biswadip Basu Mallik, Gunjan Mukherjee, Rahul Kar, and Youqing Fan; individual chapters, the contributors.