Various performance measures have been developed for performance evaluation of the stratified Thermal Energy Storage (TES) tank. There are many methods which have been developed including numerical, analytical to determine the TES tank efficiency using Figure of Merit (FOM) and Thermocline Thickness (WTC) parameters as the performance indicators. However, these methods are more complicated and need more technical data. Therefore, a simple and easy method is required to predict the performance of TES tank. In this paper, a comparative study using results from analytically solved sigmoid dose response function and artificial neural network (ANN) is conducted to determine the parameters. © 2018 Author(s).