Nowadays, Supply Chain Management (SCM) is one of the most important and complex issues for automakers in the world. The main objectives of this research were to investigate the factors that predict strategic performance of supply chain by doing quantitative research at Iran Khodro Company (IKCO) in Iran. Based on supply chain theories, strategic performance of supply chain was predicted by Information Technology (IT), Organizational Learning (OL), and Product Innovation (PRI) in our research at the first time in an automotive company. Stratified random sampling was used to determine the sample size. Accordingly, 250 questionnaires were distributed among experts and supply chain specialists at IKCO. According to Supplying Automotive Parts Company (SPSC) variable as the main dependent variable, Path Analysis (PA) technique was used to explore casual relationships among variables using multiple regression analysis in SPSS. The Confirmatory Factor Analysis (CFA) was utilized based on Maximum Likelihood (ML) analysis of normality, outliers, composite reliability, and validity to test hypotheses by using AMOS. PA, measurement model, and structural model were analyzed in order to examine the conceptual model. The results from multiple regression, path analysis, and Structural Equation Modeling (SEM) were same. Thus, all hypotheses were supported by SPSS and SEM analyses. The findings of the study are discussed in detail.