Background: Bladder cancer (BC) is a heterogeneous disease with high recurrence rate. The depth of response to platinum-based chemotherapeutic agents in urothelial neoplasm tissues varies greatly. Biomarkers that have practical value in prognosis stratification and early determination of therapeutic effect are increasingly needed. Our study aimed to select a set of BC-related genes involved in both platinum resistance and survival, then use these genes to establish the prognostic model.Methods: Platinum resistance-related DEGs and tumorigenesis-related DEGs were identified. Among the intersection of them, 10 most predictive genes were acquired through Cox, lasso, and stepwise regressions followed by building a risk score model with their regression coefficients. Survival analysis and ROC plot were used to evaluate the predictive accuracy of our model. Combined with age and TMN stages, a nomogram was generated to create a graphical representation of survival rates at 1-, 3-, 5-, and 8-year in BC patients. The prognostic performance of risk score was also validated in three independent BC datasets including cisplatin-treated patients and a gastric cancer cohort with platinum-based chemotherapy. The potential mechanism of the gene-based model was explored by enrichment analysis.Results: PPP2R2B, TSPAN7, ATAD3C, SYT15, SAPCD1, AKR1B1, TCHH, AKAP12, AGLN3, and IGF2 were selected for our prognostic model. Patients in high- and low-risk groups exhibited a significant survival difference (HR = 2.7, p < 0.0001). The prognostic nomogram of predicting 3-year OS for BC patients could yield an AUC of 0.819. In the external validation dataset, the risk score also has a robust predictive ability. Conclusion: A prognostic model derived from platinum resistance-related genes was constructed, we confirmed its value in predicting platinum-based chemotherapy benefits and overall survival for BC patients. The model might assist in therapeutic decisions for bladder malignancy.Subjects: Urology, Oncology, Bioinformatics, Molecular Biology.