〔Abstract〕 Objective Review the independent risk factors of postoperative recurrence in surgical treatment of bladder cancer patients to construct a model of bladder cancer recurrence. Methods A total of 240 surgically treated bladder cancer patients were followed up for at least 1 year and divided into recurrence(n=54) and non-recurrence(n=186).The general data of patients were comparative analyzed, and the different and statistically significant data were further analyzed by ROC curve, and the statistically significant data were included in the multivariate analysis after logistic obtaining univariate analysis results.Risk factors were included in the model construction, and the model correction curve and clinical net benefit analysis were analyzed.The model could be used to predict postoperative recurrence in bladder cancer patients. Results The ROC curves of the statistically significant continuous variables were analyzed in the general data, and the results showed that the AUC of PNI,BLCA-4,BTA,NMP22 and CEA were 0.932,0.979,0.998,0.677 and 0.981,respectively, and the optimal truncation values were ≤40.18%,>140.04 ng/mg, ≤7.22 U/mg,>7.68 μg/mg, and>1.99 ng/mg, respectively.Statistically significant data from univariate analysis were incorporated into the logistic regression model, and the results showed that PNI ≤40.18%,BLCA-4>140.04 ng/mg, BTA≤7.22 U/mg, NMP22>7.68 μg/mg was a risk factor for recurrence in patients with bladder cancer.Subsequently, PNI,BLCA-4,BTA,and NMP22 were incorporated into the construction of the model as predictors of recurrence in patients with bladder cancer.Based on the model correction curve and clinical net benefit analysis, the internal verification results showed that the C-index of the model predicting bladder cancer recurrence was 0.296(95%CI: 0.078-1.329).The calibration curve showed good consistency between the observed and predicted values.The model predicted a risk threshold>0.128 for patients with bladder cancer, and the model provided a clinical net benefit; in addition, the model had a higher clinical net benefit than PNI,BLCA-4,BTA,and NMP22. Conclusion The model correction curve and clinical net benefit analysis, the results of internal verification show that the model can be used to predict recurrence in patients with bladder cancer.