Part cooling parameters such as coolant flow rate and coolant temperature has been shown to have an important influence on the part quality in plastic injection molding. Molders commonly manipulate the coolant flow rate in an unclear manner to adjust part quality and reduce the overall cycle time. Manipulating such parameters effectively can indirectly control part quality when deviations in the injection processing variables occur if it is done in a controlled manner. In this investigation, coolant flow rate is selected to be the manipulated variable that affects an average temperature of the part surface as it cools within the mold cavity. The average part temperature is the controlled variable and its control represents the indirect control of part quality. Experiments were conducted to quantify the effects of coolant flow rate on the part surface temperature demonstrating that it is highly nonlinear and its control would require an advanced control scheme. An adaptive online modeling algorithm that uses information from temperature and flow rate sensors was developed to continuously retune a predictive controller for controlling the part surface temperature. Good control performance was obtained from the adaptive strategy for tracking setpoint changes in the part temperature and when the cooling cycle was reduced from 16 to 14 s.