Soil hydraulic parameters are needed in most projects on transport and fate of pollutants. Pedotransfer procedures are often used to estimate soil hydraulic properties from basic soil data available from soil surveys. Soil particle size distribution, or texture, is known to be a leading soil property affecting soil ability to retain and transmit water and solutes. A substantial effort has been put in searching for texture parameters useful for estimating soil hydraulic properties. Recently a new, entropy-based index has been proposed that characterizes the non-evenness of particle size distributions. This index called balanced entropy has a potential to reflect probable packing of soil particles. Our objective was to see whether the balanced entropy can serve along with other basic soil properties as one of variables-predictors of soil water retention. We computed the balanced entropy for 9871 soil samples in the NRCS soil characterization database and applied the data mining tools to estimate water retention from soil textural composition, organic carbon content, and bulk density. The balanced entropy was the best single predictor and the most important predictor of volumetric water contents at −33 kPa, which are notoriously difficult to estimate. Using the balanced entropy is a promising approach to improve the accuracy of estimated soil hydraulic properties.