In this work, a unique approach for designing a nonlinear regression model-based predictive controller (NRPC) for controlling the injection speed of 150 tonne injection molding machine. The innovation of this strategy is that the controller structure allows nonlinear open-loop modeling to be conducted while closed-loop control is executed every sampling instant. Consequently, the system matrix is regenerated every sampling instant using a continuous function providing a more accurate prediction of the plant. The proposed algorithm is implemented on controlling the screw speed for injecting plastic into a mold and controlling the temperature of three steel cylinders inside a barrel in order to melt the plastic. The experimental closed-loop responses of the proposed algorithm were compared to a multi-model dynamic matrix controller (DMC) with improved results for various setpoint trajectories. Good disturbance rejection was attained resulting in improved tracking of multi-setpoint profiles in comparison to multi-model DMC.