This study develops predictive models for adsorption of organic compounds (OC) by microplastics using linear solvation energy relationship (LSER). The adsorption mechanism of aromatic OCs by microplastics was investigated by delineating the effect of molecular weight of the OCs, polymer type of MPs, and background water chemistry. The benchmark model for adsorption of OCs (n = 28) by polyethylene yielded an R2 = 0.85 (n = 28), RMSE = 0.38, Q2LOO = 0.73. Further narrowing the dataset down by decreasing the molecular weight cutoff to OCs < 192 g/mol improved the model to R2 = 0.98 (n = 13). Validation techniques tested the predictive strength of the benchmark model, which included new experimental adsorption data and performing leave-one-out cross validation. Among LSER model descriptors, the molecular volume was the most predominant descriptor in all scenarios, suggesting the importance of non-specific interactions and OC hydrophobicity. The results demonstrated that LSER is a promising approach for predicting the adsorption of aromatic OCs by MPs.