Background: Early school dropout is an economic, social, and individual problem. School dropout is a result of cumulative processes that occur over many childhood years. Despite the influence of level of education on health outcomes, primary prevention of dropout outside of the school setting is rare. In the Netherlands, the Youth Health Care (YHC) service may play a role in primary prevention of school dropout. Objective: We hypothesized that data collected by YHC on family background and Strength and Difficulties Questionnaire (SDQ) scores at ages 10 and 14 is predictive of school dropout. Methods: We analyzed Dutch YHC data from 24,988 children born in 1996-2001. Early school dropout was defined as having left school without diploma by the age of 17. Two multilevel logistic regression models were built with predictors measured at the ages of 10 and 14. The model performance was assessed using ROC curve. Results: A child's SDQ was a strong predictor of early school dropout, in addition to gender and parents' socio-economic status at age 10 and age 14. Models showed moderate prediction performance (ROC value 0.70/0.69, respectively). Conclusions: The proposed prediction models are based on only few routinely collected socio-demographic factors and SDQ scores. We found these models can contribute to risk stratification by YHC as early as age of ten. This provides a window of opportunity for interventions that aim to strengthen school engagement. Further research and practical efforts to expand the set of predictors available to YHC (e.g., school performance) are expected to improve the quality of this prediction.