The limited availability and variability of data related to the overall degradation of compounds in the environment is a very relevant issue in studies related to environmental fate and chemical behavior. The studied phenol data set consists of reaction rate constants of different oxidation reactions in surface waters, available either experimentally or, to fill the data gap, from our QSAR models reported herein. A PCA (Principal Component Analysis) model based on these oxidative degradations has been proposed to evaluate the degradability of chemicals. The score of the first Principal Component is modelled by theoretical molecular descriptors to obtain a multiple linear regression (MLR) model with high predictive power, both internally and externally validated. This modeling approach allows a fast and preliminary ranking of phenols according to their tendency to be degraded by oxidants in water, starting only from knowledge of their molecular structure.