The purpose of this study is to estimate the ability of ML models to predict the effect of migraine preventives. This will be achieved by first identifying sociodemographic, headache and comorbidity features of migraine patients. Headache days will then be measured for 4 weeks before starting a migraine preventive, and this will be compared to the number of headache days in the first 12 weeks (divided into 28-day periods) after starting treatment. The preventive is regarded as effective if there is a 50% or greater reduction in monthly headache days. After observation of the treatment period, the ML models will use the sociodemographic, headache and comorbidity features, captured before treatment was initiated, to predict treatment effect for all preventives in each participant. These predicted treatment effects will be compared to the actual treatment effects that were observed.