The purpose of this study was to identify key autophagy-related genes (ARGs) in patients with renal cancer (RC) by bioinformatics analysis, and to clarify their potential prognostic value. Thirty-eight differentially expressed ARGs were identified between RC and normal tissues based on The Cancer Genome Atlas database. Functional enrichment analysis suggested that autophagy may play a tumor-promoting role in the initiation of RC. We established a prognostic model with two ARGs (CASP4 and BIRC5) demonstrating significant correlations in expression levels with patient overall survival (OS). Multivariate Cox regression analysis showed that age and the autophagy genes prognostic model were independent prognostic factors for patients with RC. Considering the known prognostic significance of clinical stage in RC, we constructed a nomogram based on age, clinical stage, and the prognostic model. The prognostic model was verified in a separate validation set and external cohort of patients from Beijing Hospital. Patients of low and high risk were defined based on the median risk value calculated by the model and the high risk appeared associated with a significant shorter OS (P < 0.01). Overall, our findings reveal that ARGs have potential prognostic value in patients with RC, providing new directions for targeted therapy.