Given simulated pharmacy claims data, we build and test different models of predicting the copayments required of patients ahead of time. Then we computed and provide the potential formulary status of the medication on each insurance plan. Our drug recommendation based on the highest formulary status would allow for substitute drugs in the situation when the drugs are not covered by insurance or are too expensive for patients to afford. With simulated data, our drug recommendation would save patients’ out-of-pocket expenses by $20.5 on average. The greatest savings we found was $241.55.