In this research, the authors present the tuning and implementation of the nonlinear moving average autoregressive-linearization level 2 (NARMA-L2) controller for a shell and tube heat exchanger (STHE) temperature process. A mathematical model of the process plant is considered for simulation, and the model is discretized for the controller operation. The NARMA-L2 controller computes a sequence of control variable (the cold water inflow rate) adjustments in order to optimize the future performance of STHE process. The selected controller is trained to provide a quick control over the process variable in the nominal operating range of STHE by selecting appropriate constraints for NARMA models. The paper compares the performance of the selected NARMA-L2 controller with that of a benchmark controller, and the comparative results are presented.