To build the RPLC classification model, it was assumed that the chemicals are in solution and that the chemicals can be injected into a system. Additionally, the model focuses on whether an analyte could be analyzed with RPLC regardless of experimental parameters or sample pretreatment. The dataset for this was comprised of 5167 'inside', 620 'maybe' inside, and 3999 'outside' chemicals for the RPLC subspaces. The 'outside' cases were obtained from NORMAN SusDat with extreme XLogP values, while the 'inside' and 'maybe' cases came from the three r i regression models. In figures S10, S11, and S12 the extrapolation limits for each of the models are defined. For r i range for the 'inside' RPLC subspace for the amide, UoA, and cocamide series were 350-900, 100-900, and 250-1300, respectively.