<p>A group of psychoactive substances, cathinones have become popular in the pharmaceutical and recreational arenas. Nevertheless, their large potential to abuse them and the health risks involved have caused them to become a matter of concern. Knowledge of how the structure of a molecule correlates with a specific physicochemical or pharmacological property is needed to predict the behavior and effects of a given property. We are using different topological indices as molecular descriptors and linear regression models to quantitatively analyze their effects on the essential properties of cathinone derivatives in this work. The presented quantitative structure–property relation (QSPR) analysis reveals the way structural properties control key physicochemical properties, suggesting promising information about the design and risk evaluation of cathinone-based compounds.</p>