Controlled trials in clinical psychopharmacology may fail to provide reliable information about the benefit of treatment for the patient when considered in a real-life setting rather than as a part of a well-defined sampling procedure. Previously, we applied the mathematical model of an artificial neural network (ANN) to a pool of clinical information gathered through case descriptions provided by senior psychiatrists in clinical charts of patients receiving their first exposure to sertraline. In the present study, we applied the same mathematical model to a larger sample. The performance of the ANN model in forecasting successful and unsuccessful treatment showed an overall accuracy of classification of 97.12%. This result supports our previous finding about the potential application of this method as a reliable predictor of a given psychiatric patient's outcome during a specific psychopharmacological therapy.