Supply chain sustainability means managing the flow of goods, data, and capital throughout the production and distribution process, in a way that minimizes negative environmental impacts and respects social and economic responsibilities throughout the product life cycle. This approach is not limited to reducing carbon footprints or optimizing energy consumption, but also includes creating ethical transparency in the supply of raw materials, ensuring humane working conditions in all links in the chain, and increasing resilience to crises to ensure long-term business survival. In this regard, this research aimed to model the improvement of supply chain sustainability performance in the country's steel industry under conditions of uncertainty in the steel industries of Khuzestan Province. The method of this research was mixed (qualitative-quantitative). In the qualitative section, the meta-synthesis method was used to identify indicators, and after reviewing 86 articles, 29 articles were finally used as the basis for extracting indicators, and the analysis of qualitative data led to the extraction of 12 indicators. Then, in the quantitative section, fuzzy DANP-ISM was used for modeling. The data in this section were collected with the help of a self-interaction matrix, which was completed by 26 experts. As a result, the analysis of the collected data with ISM Matlab software resulted in a five-level model, the most effective indicator of which is the comprehensive sustainability program.