This study describes a fuel quality prediction strategy that predicts the fuel quality parameter and component composition of Renewable Natural Gas (RNG) containing CH4, C2H6 and CO2. Onsite measurement of the gas properties in a renewable natural gas (RNG) fuel is necessary to ensure an expected level of quality, which must be maintained for better combustion efficiency. The Wobbe Index (WI) and methane number (MN) are the natural gas quality indicators used. To predict the WI, MN, and component composition, a data set that consists of WI, MN, thermal conductivity and sound velocity of the gaseous fuel mixture as a function of its temperature, pressure and composition, was created. Through a regression analysis of the data set, a model that estimates the WI, MN and composition of the gaseous fuel mixture from its physical properties (temperature, pressure, thermal conductivity and sound velocity), was developed. The results of the study including the data set and the prediction model that can accurately estimate the WI, MN, and gas composition, is presented in this paper.