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Renal transplantation is the only efficacious treatment for end‐stage kidney disease. However, some people have developed renal insufficiency after transplantation, the mechanisms of which have not been well clarified. Previous studies have focused on patient factors, while the effect of gene expression in the donor kidney on post‐transplant renal function has been less studied. Donor kidney clinical data and mRNA expression status were extracted from the GEO database (GSE147451). Weight gene co‐expression network analysis (WGCNA) and differential gene enrichment analysis were performed. For external validation, we collected data from 122 patients who accepted renal transplantation at several hospitals and measured the level of target genes by qPCR. This study included 192 patients from the GEO data set, and 13 co‐expressed genes were confirmed by WGCNA and differential gene enrichment analysis. Then, the PPI network contained 17 edges as well as 12 nodes, and four central genes (PRKDC, RFC5, RFC3 and RBM14) were identified. We found by collecting data from 122 patients who underwent renal transplantation in several hospitals and by multivariate logistic regression that acute graft‐versus‐host disease postoperative infection, PRKDC [Hazard Ratio (HR) = 4.44; 95% CI = [1.60, 13.68]; p = 0.006] mRNA level correlated with the renal function after transplantation. The prediction model constructed had good predictive accuracy (C‐index = 0.886). Elevated levels of donor kidney PRKDC are associated with renal dysfunction after transplantation. The prediction model of renal function status for post‐transplant recipients based on PRKDC has good predictive accuracy and clinical application. [ABSTRACT FROM AUTHOR]