Objective:To establish a carbohydrate metabolism-related genes(CRGs)prognostic model for clear cell renal cell carcinoma(ccRCC)and investigate its clinical value.Methods:ccRCC mRNA expression data were sourced from The Cancer Genome Atlas(TCGA)data-base.CRGs were retrieved from the MSigDB and KEGG databases.A prognostic model based on CRGs was constructed using the LASSO lin-ear regression model,and the risk score(RS)was calculated.Patients were assigned into high-and low-risk groups according to the median RS.Differences in survival,immune infiltration,mutation,and immune response between the two groups were analyzed using Kaplan-Meier curves and bioinformatics methods.Constructing a nomogram based on the RS and clinical features and validating its accuracy of prognostic predictions.The expression of CRGs in the ccRCC samples was detected using RT-qPCR.Results:A total of eight key genes were utilized to construct a prognostic risk model for ccRCC.Survival analysis revealed that patients in the low-risk group had a better prognosis(P<0.001).Bioinformatics analysis showed that the RS correlated with immune cell infiltration,mutation,and immune responses.The nomogram based on the RS and clinical features demonstrated a strong predictive ability for prognosis.In vitro experiments confirmed notable differences in the expression of the eight CRGs between ccRCC and adjacent non-malignant tissues.Conclusions:A prognostic model based on CRGs can effectively predict the prognosis of patients with ccRCC.