<p>Nowadays, the widespread demand for environmental protection and clean production has compelled organizations to pay special attention to evaluating and selecting suppliers aligned with sustainability and circular principles. Supply chain management (SCM) processes extend from the supplier’s suppliers to the end consumer. Therefore, suppliers, as the first layer in production and operations processes, play a crucial role in achieving clean production. The application of circular economy principles in SCM concepts has led to significant outcomes, including circular supply chain management and circular supplier selection (CSS). Given that the application of circularity concepts in SCM is relatively new, either recently implemented or anticipated for the future, there are high levels of uncertainty associated with these issues. Therefore, the main objective of this study is to propose an approach for CSS under high levels of uncertainty. The proposed approach involves developing the simplified best–worst method within an interval-valued Fermatean fuzzy Z-numbers environment that simultaneously leverages the advantages of interval numbers, Fermatean fuzzy sets, and Z-numbers to handle high levels of uncertainty. The proposed approach was applied in a case study with real-world conditions in the cellulose industry to prioritize decision criteria and rank suppliers. The results revealed that criteria C₁, C₆, and C₅ were the most influential criteria in circular supplier evaluation, while supplier S₃ achieved the highest ranking among the considered suppliers. Ultimately, sensitivity analysis is conducted to examine the robustness of the results, and comparative analysis is performed to validate the proposed approach.</p>