Objective: To explore the influencing factors of mild dysplasia in patients with ulcerative colitis and to construct a nomogram model. Methods: The clinical data of 315 patients with ulcerative colitis admitted to our hospital from September 2020 to September 2023 were retrospectively collected. According to the occurrence of mild dysplasia in the patients, they were divided into the group with mild dysplasia and the group without mild dysplasia. Collect and compare the baseline data of the two groups. Logistic regression analysis was used to analyze the factors influencing mild dysplasia in patients with ulcerative colitis. Based on the results of Logistic regression analysis, a nomogram risk prediction model was constructed using R software, and the receiver operating characteristic (ROC) curve was plotted to evaluate the predictive efficacy of the nomogram prediction model. Result: Among 315 patients with ulcerative colitis, 41 patients presented with mild dysplasia, and 274 patients did not present with mild dysplasia. There were no significant differences in age, body mass index, disease duration, serum albumin, hemoglobin levels, gender, drug treatment status, family history of colorectal cancer, smoking history, drinking history, diabetes, and hypertension between the group with mild dysplasia and the group without mild dysplasia (P > 0.05). There were significant differences in serum procalcitonin level, lesion location, disease activity degree, and the presence of primary sclerosing cholangitis between the group with mild dysplasia and the group without mild dysplasia (P < 0.05). Logistic regression analysis showed that high serum procalcitonin level, lesion site of the entire colon, severe disease activity, and accompanied by primary sclerosing cholangitis were risk factors for mild dysplasia in patients with ulcerative colitis (all OR > 1, all P < 0.05). A nomogram prediction model for patients with ulcerative colitis complicated with mild dysplasia was constructed. The discrimination of the model was verified by the Bootstrap internal validation method, with C-index=0.943, indicating that the model has good discrimination. Draw the standard curve. If the calibration curve is close to the Y-X straight line, it indicates that the model has good accuracy. The ROC curve was drawn to verify the nomogram risk prediction model for mild dysplasia in patients with ulcerative colitis. The AUC was 0.943, and the 95%CI was 0.912-0.974, P < 0.001, indicating that this risk prediction model has good predictive efficacy. Conclusion: The influencing factors of mild dysplasia in patients with ulcerative colitis are serum procalcitonin level, lesion location, disease activity degree, and the presence of primary sclerosing cholangitis. The risk prediction model for mild dysplasia in patients with ulcerative colitis constructed based on the above factors has certain predictive value.