Improving the control strategy of an heating, ventilation, and air-conditioning(HVAC) system can result in substantial energy saving. However, it is challenging to obtain the optimal control strategy of the HVAC system due to the model's complexity. In this paper, to reduce the complexity of an HVAC system's model, we propose the regression model of the heat exchange efficiency of the cooling tower and use regression analysis to obtain the coefficients. The proposed model avoids the iterative computing process and reduces the complexity of an HVAC system's model. Numerical results show that the proposed model takes only 1% computing time to get the value of heat exchange efficiency, and the relative deviations are less than 0.4%, compared with the original model.