Objective To construct and validate a nomogram prediction model for the high-risk human papillomavirus (HPV) infection and its natural clearance in professional women. Methods Women with regular professions, who underwent professional medical examination and were confirmed with high-risk HPV infection without cervical cancer and cervical epithelial neoplasia in a hospital from March 2020 to March 2021 were studied. Patients were divided into the model group and the validation group in a 7:3 ratio. The model group were subdivided into the natural clearance group and the persistent infection group based on follow-up results. The general information, reproductive-related treatment, sexual partner-related information, and examination results of the two groups of patients were compared. Potential factors for natural clearance of high-risk HPV infection in professional women were screened out by LASSO regression. Independent influencing factors were screened out with multivariate logistic regression. Based on multivariate logistic regression results, a nomogram prediction model was constructed and validated using R programming language. Results A total of 329 cases were included, 230 in the model group and 99 in the validation group. There was no statistically significant difference in general information between the two groups of patients (all P>0.05). Among the 230 high-risk HPV infection patients in the model group, 165 turned negative at the end of follow-up, with a natural clearance rate of 71.74%. Based on LASSO regression analysis, multivariate logistic regression analysis showed that age, contraceptive method, number of sexual partners, excessive foreskin of sexual partners, initial viral load, HPV infection type, and reproductive tract inflammation were independent influencing factors for the natural clearance of high-risk HPV infection in professional women (all P < 0.05). The receiver operating characteristic (ROC) curve analysis showed that the areas under the curve (AUC) of natural clea-rance of high-risk HPV infection in professional women in the model group and validation group were 0.834 (95%CI: 0.776-0.893) and 0.817 (95%CI: 0.755-0.879), respectively. H-L goodness-of-fit test result showed that the difference between the nomogram model and the ideal model was not statistically significant (P>0.05). The calibration curve results showed that the predicted curves of the model group and validation group were basically fit with the standard curve, indicating a high predictive accuracy of the model. The decision curve analysis results of the model group showed that when the probability threshold of natural clearance of high-risk HPV infection in professional women predicted by the nomogram model was 0.15-0.95, the net benefit rate of patients was >0. Conclusion The natural clearance rate of high-risk HPV infection in professional women is high, mainly influenced by factors such as age, contraceptive method, and number of sexual partners. The nomogram model constructed in this study has high accuracy and discrimination in predicting the natural clearance rate of high-risk HPV infection in professional women.