In the process of manufacturing rubber parts for the automotive industry using extrusion techniques, leftover rubber is often found during the process, which may result in non-recyclable waste and negatively impact the environment. The risk assessment of the green supply chain is a tool designed to control and prevent issues during the rubber production process. The risk assessment of the green supply chain includes risks related to reliability, responsiveness, agility, cost, and asset management efficiency, which are taken into consideration for implementation. This study presents an integrated scientific model that uses Fuzzy Failure Mode and Effects Analysis (Fuzzy FMEA) alongside Artificial Neural Networks (ANN) to analyze indices and prioritize risks within the rubber manufacturing process. The goal is to address uncertainties and risks occurring during the rubber extrusion process of the selected case study company. To effectively manage and mitigate issues in the rubber manufacturing process, it is essential to carefully consider the risks associated with the green supply chain, including reliability risk, responsiveness risk, agility risk, cost risk, and asset management efficiency risk. This study proposes an integrated scientific model by applying Fuzzy Failure Mode Effect Analysis (Fuzzy FMEA) with Artificial Neural Network (ANN) for analyzing the index and priority of risks in the rubber manufacturing process to assess the uncertainty and risks posed during the rubber extrusion process of a selected company as a case study. From the model developed to address the issues found in the rubber manufacturing process using extrusion techniques, based on the risk assessment of the green supply chain with appropriate criteria, when tested with the selected case study company, The company successfully reduced production costs, improved efficiency, and effectively planned weekly production while controlling costs.