The adsorption of 12 pesticides of the phenylurea family was studied by batch experiments in order to determine the adsorption coefficient, K d. The study was conducted in two soils chosen for their differences in organic matter and calcite contents. K d pesticide adsorption coefficients were higher for soil S1 than for soil S2 due to the presence of a higher organic matter content and a lower calcite content in soil S1. To identify pesticide properties governing retention, 18 molecular descriptors were considered. Class-specific quantitative structure-property relationship (QSPR) soil sorption models using one, two, and three descriptors were developed from our experimental data using linear regressions. One of the aims of this work was to check whether QSPR models that did not include literature values of K ow were able to predict K d coefficients in satisfactory agreement with our experimental data. The influence of the level of theory in determining K ow and polarisability predictors on the predictive performance of the model was also examined by comparing quantum chemistry and empirical (QikProp) approaches. The one-descriptor model using "quantum" polarisability α was found to perform almost as well as or better than the other models.