Chlorinated paraffins (CPs) are highly complex mixtures of polychlorinated <i>n</i>-alkanes with differing chain lengths and chlorination patterns. Knowledge on physicochemical properties of individual congeners is limited but needed to understand their environmental fate and potential risks. This work uses a sophisticated but time-demanding quantum chemically based method COSMO-RS and a fast-running fragment contribution approach to enable prediction of partition coefficients for a large number of short-chain chlorinated paraffin (SCCP) congeners. Fragment contribution models (FCMs) were developed using molecular fragments with a length of up to C<sub>4</sub> in CP molecules as explanatory variables and COSMO-RS-calculated partition coefficients as training data. The resulting FCMs can quickly provide COSMO-RS predictions for octanol–water (<i>K</i><sub>ow</sub>), air–water (<i>K</i><sub>aw</sub>), and octanol–air (<i>K</i><sub>oa</sub>) partition coefficients of SCCP congeners with an accuracy of 0.1–0.3 log units root mean squared errors. The FCM predictions for <i>K</i><sub>ow</sub> agree with experimental values for individual constitutional isomers within 1 log unit. The distribution of partition coefficients for each SCCP congener group was computed, which successfully reproduced experimental log <i>K</i><sub>ow</sub> ranges of industrial CP mixtures. As an application of the developed FCMs, the predicted <i>K</i><sub>aw</sub> and <i>K</i><sub>oa</sub> were plotted to evaluate the bioaccumulation potential of each SCCP congener group.<br>
Predicting Partition Coefficients of Short-Chain Chlorinated Paraffin Congeners by COSMO-RS-Trained Fragment Contribution Models