Objective: This study aims to use the data in the Cancer Genome Atlas (TCGA) database to construct a survival prognostic model composed of M5C-related genes, and to analyze the independent prognostic factors related to the survival of clear cell renal cell carcinoma to predict Prognosis of patients with renal clear cell carcinoma.Methods: The data of patients with renal clear cell carcinoma were downloaded from the TCGA database, m5C-related genes were obtained from the published literature, and their differential expression between the tumor group and the control group was analyzed. Consensus clustering analysis of these genes was then performed to reveal the relationship between m5C-related genes and prognosis in clear cell renal cell carcinoma. A survival prognostic model was constructed by univariate Cox analysis and Lasso-Cox regression analysis to analyze the prognostic factors associated with renal clear cell carcinoma. Finally, GO and KEGG enrichment analysis was performed to further explore biological functions and potential signaling pathways .Results: We found that m5C-related genes were differentially expressed between the tumor group and the normal group in renal clear cell carcinoma. The results of consensus clustering analysis showed that the prognosis of patients with clear cell renal cell carcinoma in cluster 1 was better than that in cluster 2. The constructed survival prognostic model divided clear cell renal cell carcinoma into high-risk group and low-risk group. Univariate and multivariate Cox analysis showed that grade and stage may be independent prognostic factors for clear cell renal cell carcinoma. GO and KEGG analysis showed that m5C-RNA modification helps to regulate the progression of renal clear cell carcinoma.Conclusion: According to the research, the survival prognostic model of M5C-related genes constructed by us can predict the prognosis of patients with clear cell renal cell carcinoma