We present an approach to model the dynamic of a copper flotation process. The conventional approach of system identification is applied to model the dynamics. In this research, experiments are performed to collect process data of determined input and output variables. It is followed by data pre-processing to handle outliers and to remove high frequency disturbances. Simulation and validation responses of linear estimated models, which captured the dynamic of the process, are presented. The long term goal is to use estimated models to design a models-based control system.