Given the increasing complexity of supply chains and the importance of the role of suppliers in improving the economic and environmental performance of organizations, selecting appropriate suppliers in large and reverse supply chains has become one of the fundamental challenges of manufacturing industries. The steel industry, as one of the parent industries, needs to use modern and systematic models in this area more than other industries. Therefore, the main goal of this research is to identify and classify the components affecting the selection of suppliers in the large and reverse supply chains in the steel industries of Chaharmahal and Bakhtiari province using the method of content analysis and interpretive structural modeling. This research is applied and mixed. Initially, through semi-structured interviews with 12 managers of the steel industry of Chaharmahal and Bakhtiari province and university professors who were selected by theoretical sampling method, the components were identified, data were collected and codes were collected, the components affecting the selection of large and reverse supply chain suppliers in the steel industry of Chaharmahal and Bakhtiari province were counted in 5 main categories and 12 subcategories and compiled in the form of a thematic analysis network. The method of analyzing the information in the quantitative part included interpretive structural modeling. The results of the quantitative part showed that there are 12 components affecting the selection of large and reverse supply chain suppliers, of which two sub-criteria of improving brand image and environmental pressures, demand management techniques and risk management resulting from sudden changes have the highest level and the most impact. And the sub-criteria of customer orientation has the lowest level and the most impact. The presented model can provide significant help and guidance to managers in selecting the most appropriate large and reverse supply chain suppliers.