This study provides an analysis of the reliability of five mathematical models, simulating permeation of substances through the skin from aqueous solutions. An extensive database was generated, containing data on 123 measured permeation coefficients of 99 different chemicals and their physicochemical properties. In addition, in this database all relevant experimental conditions are included. The coefficients of the different skin permeation models were estimated by non-linear multiple regression, using the octanol-water partition coefficient and the molecular weight as independent parameters. The reliability of the models was evaluated by testing variation of regression coefficients and of residual variance for subsets of data, randomly selected from the complete database. Three models were considered to provide reliable estimations of the skin permeation coefficient. These are based on the McKone and Howd model, the Guy and Potts model and the Robinson model. The last-mentioned two models were adaptations, because MW0.5 as independent parameter provided a better fit than MW (MW = molecular weight) in the original models. The McKone and Howd model and the Robinson model have the advantage, that they predict more precisely the skin permeation of highly hydrophilic and highly lipophilic chemicals compared to the Guy and Potts model. The revised Robinson model resulted always in the smallest residual variance.