Natural gas is an important source of energy. It is efficient, versatile and abundantly available. Calcium chloride (CaCl2) dehydrator is the most common non-regenerative adsorption system in natural gas industry. As the need for natural gas increases, calcium chloride dehydration can help to make some gas wells more profitable to operate gas from remote or offshore wellheads, gas of a low flow rate, or gas which is high in sulphur content may benefit from this dehydration. In this article two mathematical-based models are developed to estimate approximate water content of natural gas dried by calcium chloride dehydrator units for both freshly recharged and just prior to recharging conditions as a function of temperature and pressure. Firstly, a simple empirical correlation is presented to estimate water content of natural gas dried by solid calcium chloride dehydrator, Secondly, a multilayer perceptron (MLP) neural network is developed for the same calculations. The results of both presented models are found to be in excellent agreement with reported data in the literature. The tools developed in this study can be of immense practical value for engineers to have a quick check on water content of natural gas dried by calcium chloride dehydrator units as a function of dehydrator temperature and pressure at various conditions without opting for any experimental trials. In particular, engineers would find the approaches to be user-friendly with transparent calculations involving no complex expressions. (C) 2013 Elsevier Ltd. All rights reserved.