The detergency effect has been examined for a series of technical nonionic surfactants with the use of statistical experimental designs and revealed a plateau in each of the response surfaces obtained. The surfactant concentrations and washing temperatures, needed to reach the edge of each detergency effect plateau, were also determined. These conditions, which define the edge of the plateau, could be well modeled from the physicochemical properties of the surfactants with the use of partial least squares of latent structures. It was also possible to point out the importance of the different physicochemical properties. If an experimental design has been utilized, the detergency effect of a nonionic surfactant can be modeled from multiple linear regression as a function of surfactant concentration, washing time, and washing temperature. We have shown how these regression coefficients can be modeled from the physicochemical properties of the surfactants. Partial least squares of latent structures were used to estimate these models as well. We also demonstrated how these models can be used to predict the regression coefficients of a surfactant not included in the model estimations. The resultant regression coefficients can then be used to predict the detergency effects of this surfactant at different variable settings. The detergency effects thus obtained are in good agreement with measured data acquired under corresponding conditions.