Objectives：To develop and validate the risk prediction model for cervical intraepithelial neoplasia grade 2 or worse （CIN2+），and provide guidance for the treatment of cervical lesion. Methods：The clinical and pathological data of 1 266 patients who underwent cervical biopsy from January 2015 to December 2017 were retrospectively analyzed，and histopathological examination was used as the golden standard for the final diagnosis. A logistic regression analysis was used to identify the risk factors for predicting CIN2+，the disease risk prediction model and individualized prediction nomogram were developed，and the predictive performance and concordance of the model and nomogram were evaluated，respectively. Results：①The results of chi-square test showed that the risk factors for CIN2+ were smoking history（ χ2=29.92，P=0.000），ThinPrep cytology test（TCT）（χ2=172.89，P=0.000），human papillomavirus （HPV）（ χ2=147.03，P=0.000），colposcopy results（ χ2=340.85，P=0.000），and the ratio of lesion area to cervical area（ χ2=206.22，P=0.000）. ②The regression model was developed through multivariate logistic regression analysis，and the area under the curve of the model was 0.88. ③The nomogram was developed，and its index of concordance was 0.878 after internal validation. Conclusion：The regression model developed in the study is based on the five risk factors of smoking history，TCT，HPV，colposcopy results，and the ratio of lesion area to cervical area，with good performance and accuracy in predicting CIN2+ risk，and can help to establish individualized treatment plans.