In recent years, the field of computational psychiatry has made progress in the modeling of diseases using reinforcement learning. In this study, we focus on the placebo effect. Specifically, we attempt to model the placebo effect using reinforcement learning on the open data of a probabilistic reward task. We model the placebo effect induced by non-invasive brain stimulation techniques such as transcranial near infrared laser stimulation and transcranial direct current stimulation. The accuracy of the obtained models is verified by numerical simulations.