A group of European gas transportation companies within the European Gas Research Group launched in 2007 the 'MOLAS' Project to provide a software program for the analysis of the Liquefied Natural Gas (LNG) ageing process during ship transportation. This program contains two different modeling approaches: a physical algorithm and an 'intelligent' model. Both models are fed with the same input data, which is composed of the ship characteristics (BOR and capacity), voyage duration, LNG composition, temperature, pressure, and volume occupied by liquid phase at the port of origin, together with pressure at the port of destination. The results obtained are the LNG composition, temperature and liquid volume at the port of destination. Furthermore, the physical model obtains the evolution over time of such variables en route as it is based on unsteady mass balances over the system, while the i-model applies neural networks to obtain regression coefficients from historical data composed only of origin and destination measurements. This paper describes both models and validates them from previous published models and experimental data measured in ENAGAS LNG regasification plants. (C) 2009 Elsevier Ltd. All rights reserved.