Abstract: Objective To explore the risk factors influencing the surgical success of arteriovenous fistula in patients with uremia, and establish the regression model predicting the surgical success. Methods 108 patients with end-stage nephropathy admitted to Department of Nephrology, Longyan Second Hospital from Jan. 2015 to Nov. 2017 were retrospectively analyzed. The patients' basic information, and vascular inner diameter, velocity and arterial intima-media thickness under the color ultrasound were collected. The forearm arteriovenous fistula was made by 2 skilled nephrologic physicians. The surgical success served as dependent variable, and each independent variable was subjected to the univariate analysis. The meaningful independent variables were given the multivariate non-conditioned Logistic regression analysis, and the Logistic regression model was creased. OR of each factor was calculated, and receiver operating characteristic curve (ROC) was used to evaluate the accuracy, sensitivity and specificity of the model predicting the surgical success rate. Results The univariate Logistic regression analysis revealed that the average systolic pressure (P=0.001), fibrinogen (P=0.016), total cholesterol (P=0.003), diabetic mellitus (P=0.000), inner diameter of radial artery (P=0.017), inner diameter of cephalic vein (P=0.000), and arterial velocity (P=0.000) were the factors influencing the surgical success. The regression model was built up by introducing the factors into the multivariate unconditioned Logistic regression analysis:Logit P=15.637+1.178×Total cholesterol-0.071×Radial artery velocity-81.642×Inner diameter of cephalic vein. The ROC for the model predicting the surgical success was drawn, and the area under the ROC (95% confidence interval) was 0.888 3 (0.768 3 to 1.008) (P<0.001), sensitivity was 83.33%, and specificity was 94.44%. The accuracy of the model predicting the surgical success of arteriovenous fistula was 96.3%. Conclusions Using Logistic regression analysis in combination with clinical variables, the model predicing the surgical success was established. Using the ROC, the predictive efficacy of the model was evaluated to increase the positive predictive value of the operation. This model can predict the early surgical success rate of arteriovenous fistula to some extent.