The critical role of carbonic anhydrases in different physiological processes has put this protein family at the center of attention, challenging major diseases like glaucoma, neurological disorders such as epilepsy and Alzheimer's disease, obesity, and cancers. Many QSAR/QSPR (quantitative structure–activity/property relationship) researches have been carried out to design potent carbonic anhydrase inhibitors (CAIs); however, using inhibitors with no selectivity for different isoforms can lead to major side-effects. Given that QSAR/QSPR methods are not capable of covering multiple targets in a unified model, we have applied the proteochemometric approach to model the interaction space that governs selective inhibition of different CA isoforms by some mono-/dihydroxybenzoic acid esters. Internal and external validation methods showed that all models were reliable in terms of both validity and predictivity, whereas Y-scrambling assessed the robustness of the models. To prove the applicability of our models, we showed how structural changes of a ligand can affect the selectivity. Our models provided interesting information that can be useful for designing inhibitors with selective behavior toward isoforms of carbonic anhydrases, aiding in their selective inhibition.