INTRODUCTION: Autism spectrum disorder (ASD) and schizophrenia spectrum disorder (SSD) share some symptoms. We conducted machine learning classification to determine if common screeners used for research in non-clinical and subclinical populations, the Autism-Spectrum Quotient (AQ) and Schizotypal Personality Questionnaire - Brief Revised (SPQ-BR), could identify METHODS: 1,397 undergraduates completed the SPQ-BR and AQ. Random forest classification modelled whether SPQ-BR item scores predicted AQ scores and factors, and vice versa. The models first used all item scores and then the least/most important features. RESULTS: Robust trait overlap allows for the prediction of AQ from SPQ-BR and vice versa. Results showed that AQ CONCLUSIONS: Overall, the SPQ-BR and AQ measure overlapping symptoms that can be isolated to some factors. Importantly, where we observe model failures, we capture distinctive factors. We provide guidance for leveraging existing screeners to avert misdiagnosis and advancing specific/selective biomarker identification.