Prediction of water and vapor flow in porous media requires an accurate estimation of the soil water retention curve describing the relation between matric potential and the respective soil water content from saturation to oven dryness. In this study, we modified the Kosugi (1999) function to represent soil water retention at all matric potentials. This modification retains the form of the original Kosugi function in the wet range and transforms to an adsorption equation in the dry range. Following a systems identification approach, the extended function was tested against observed data taken from literature that cover the complete range of water contents from saturation to almost oven dryness with textures ranging from sand to silty clay. The uncertainty of parameter estimates (confidence intervals) as well as the correlation between parameters was studied. The predictive capability of the extended model was evaluated under two reduced sets of data that do not contain observations below a matric potential of -1500 and -100 kPa. This evaluation showed that the extended model successfully predicted the water content with acceptable uncertainty. These results add confidence into the proposed modification and suggest that it can be used to better predict the soil water retention curve, particularly under reduced data sets.