A dynamic process model for predicting the fluidized bed roasting of copper concentrates with high arsenic content is presented in this work. Mass and energy balances were performed based on roasting mechanism derived from thermodynamic data of species. The reaction rate data, obtained from pilot plant studies on major reactions, were used in tuning the kinetic parameters of the model. IDEAS, a dynamic simulation package, is used in setting up the fluidized bed roaster plant model. The effect of process parameters such as concentrate feed rate, concentrate composition, airflow and cooling water rate on the temperature and conversion of roasting reactions are analyzed. The plant model captures the highly transient conditions occurring during the plant start-up, shutdown and other process perturbations. The application of this model in constructing a virtual plant environment for validating the operating procedures and operator training is presented.