High-risk human papillomavirus (hrHPV) assessment as a primary screening test improves sensitivity but decreases specificity. Determining risk for cervical abnormalities and adapting policy accordingly may improve the balance between screening benefits and harms. Our aim is to assess the value of factors other than HPV in prediction of cervical abnormalities. Data from a Dutch prospective cohort were used. Women aged 18–29 years, not yet eligible for screening, were included in 2007. Data collection consisted of a questionnaire and a cervicovaginal self-sample. Linkage with PALGA (pathology database) was performed in 2017. The analyses included 1483 women. The full model, including sociodemographic and lifestyle factors, was compared to the null model, including baseline HPV only. The outcome of interest was cervical intraepithelial neoplasia 2 or worse (CIN2+). There were 86 women with CIN2+. Baseline hrHPV status was an important predictor (OR = 5.20, 95%CI = 3.27–8.27). The area under the ROC curve (AUC) of the null model was 0.67 (95%CI = 0.61–0.72). The full model had a slightly higher AUC of 0.73 (95%CI = 0.67–0.79). Bootstrap validation indicated that overfitting was present. This exploratory study has confirmed that a single hrHPV measurement is a strong predictor of cervical abnormalities, and additional risk factors in young women appeared to have limited added value. However, prediction based on hrHPV only does leave room for improvement. Future studies should therefore focus on women in the screening age range and search for other predictors to further enhance risk prediction. Adapting policy based on risk may eventually help optimise screening performance.