A face-centered central composite design was applied in order to optimize the granulation process on a semi-full scale (30-kg batch) for the geometric mean granule size. The granulation process variables investigated were: inlet air temperature, inlet airflow rate, spray rate and inlet air humidity. Based on the process variables, the theoretical powder bed moisture content after the spraying process and a measure for the droplet size were determined. Multiple regression modeling was used to develop two models for the granule size: an empirical model, based on the four process parameters, and a fundamental model, based on the balance between the granule growth affected by the theoretical powder bed moisture content and the droplet size and the breakage effect of the airflow rate. These regression models were used to optimize the granulation process to obtain a granule size between 300 and 500 microm. Additional experiments confirmed that these models were valid. Other granule properties, namely the geometric standard deviation, the Hausner index, the angle of repose and the moisture content, were evaluated at the optimal operation conditions.