In view of controversial environmental issues and increased public awareness, companies are increasingly under pressure from their beneficiaries and governments to become environmentally friendly. These environmentally competitive conditions have led companies to emphasize green practices in their daily operations, and a critical aspect of environmental operations involves the selection of circular suppliers for collaboration. In this paper, a novel approach is developed by integrating multi-criteria decision-making (MCDM) methods and fuzzy inference system (FIS) to evaluate and rank the suppliers towards the transition in the circular supply chain. In the proposed approach, the weights of sub-criteria are determined based on the fuzzy analytic hierarchy process (FAHP) method and, then, the score of each supplier in terms of each criterion is calculated by the fuzzy technique for order of preference by similarity to the ideal solution (FTOPSIS). At the end, the final score of the suppliers is calculated and the suppliers are ranked using a FIS. Since each method of the above-mentioned suffers some drawbacks in addition to its unique advantages, this study attempts to overcome these disadvantages through the integration of these methods for the first time. This study contributes to the sustainable development goals (SDG's) such as Good Health, and Wellbeing (SDG 3); Clean Water and Sanitation (SDG 6); Decent Work and Economic Growth (SDG 8); Industry, Innovation and Infrastructure (SDG 9); Responsible Consumption and Production (SDG 12) and Climate Action (SDG 13). In this way, a practical approach will be proposed for ranking suppliers in the circular supply chain. This approach was applied to an Iranian petrochemical company with six suppliers involved. The performance of proposed approach is validated through comparing it with two other methods by using the Spearman rank correlation coefflcient. The results, obtained through comparisons and experts’ opinions, show that the proposed approach is efficient and applicable.