Supply chain sustainability assessment is key to maintaining and improving the performance of agroindustry supply chain, particularly in agroindustry sustainable development. Assessment of the agroindustry supply chain performance is a complex and dynamic process. Hence, there is a need for an adaptive fuzzy multi-criteria sustainability assessment model as an alternative method for analysis and improvement. This study aims to design an adaptive fuzzy multi-criteria sustainability assessment and improvement model of the sugarcane agroindustry supply chain. In this study, (1) fuzzy inference system (FIS) was developed to assess the performance of sustainability dimensions. This study proposed 24 indicators of 4 dimensions, namely, economic, social, environment, and resource. (2) Adaptive neuro fuzzy inference system (ANFIS) was designed for aggregating the overall supply chain sustainability performance. (3) The proposed fuzzy multi-criteria assessment model was compared with the common multidimensional scaling (MDS) and linear models. This study proved that the proposed synthesis of the FIS and ANFIS models was powerful and adaptive for evaluating supply chain sustainability and providing accurate results. (4) The strategy to improve sustainability performance was developed using the cosine amplitude method (CAM). The proposed model determined that the overall supply chain sustainability value was 68.58%, which is almost sustainable. Several strategies have been suggested to improve sustainability performance, including maintaining sugarcane supply by strengthening the partnership program and improving the mill's overall recovery, followed by factory revitalization or new factory investment.