Prediction of alcohol use disorder (AUD) may reduce the number of deaths caused by alcohol-related diseases. However, prediction of AUD based on patients’ historical clinical data is still an open research objective. This study proposes a method to predict AUD from electronic health record (EHR) data through supervised machine learning. The study combines EHR data with patient reported data from 2,571 patients in the Region of Southern Denmark that labels patients into two categories, AUD positive (457) and AUD negative (2,114). These unique datasets are used to validate the proposed method for prediction of AUD using machine learning methods based on historical clinical data from EHRs.