There is an increasing use of polymers in analytical chemistry as sorbents for organic chemicals in sampling, cleanup, and chromatography. In order to find the optimal polymer for a given purpose, one needs to know the equilibrium partition constants of the chemicals of interest in a wide range of polymers. COSMOtherm, a quantum-chemically based software, is designed to predict such equilibrium partition constants based only on the molecular structure as input information. In this work, literature data for such equilibrium partition constants were collected for a wide range of different polymers and used to evaluate the performance of COSMOtherm. The results show good agreement between the predicted and experimental data from water and air for most of the tested polymers. The relative preference of analytes to sorb in a given polymer represented by the molecular structure of a monomer can be predicted without any calibration. If absolute values for the partition constants are required, then a few experimental values are needed to establish a log-linear regression between the model output and the experimental values. COSMOtherm appears to be a helpful tool for selecting the best sorbent polymer for a given task or for designing new polymers. The present evaluation is limited to chemicals with a rather simple structure. Further evaluation with complex chemicals that possess multiple functionalities is still warranted.