Early diagnosis of psychiatric disorders among children can reduce the risk of adverse psychosocial outcomes in adulthood. We aimed to design a computer-aided screening tool to examine the association between modifiable risk factors and psychiatric disorders in a developing country. Ten thousand three hundred fifty students, aged 6–18 years from all Iran provinces, participated in this study. We used feature discretization and encoding, stability selection, and regularized group method of data handling (GMDH) to classify the comprehensive risk factors to depression (the prevalence of 20.1%), worriedness (23.7%), and emotional problems (11.1%). Self-rated health was the most important feature. The selected modifiable factors were eating breakfast, screentime, salty snack for depression, physical activity, salty snack for worriedness, (abdominal) obesity, sweetened beverage, and sleep-hour for emotional problems classification. The area under the ROC Curve (AUC) of the GMDH was 0.88 [CI 95%: 0.87-0.89], 0.79 [0.77-0.80], and 0.70 [0.68-0.72] for depression, worriedness, and emotional problem outcomes, respectively. The GMDH provided a deep interaction network to introduce important features that univariate modeling had not identified. It significantly outperformed the state-of-the-art (adjusted p <0.05; McNemar's test). It is thus a promising new psychiatric screening tool for children and adolescents.