Abstract: Pharmaceutical and personal care products (PPCPs) represent a novel category of pollutants that have garnered considerable attention in recent years. The ozone reaction rate (k_O3) in wastewater is a pivotal factor in evaluating the environmental risk posed by PPCPs. In this paper, we employed quantum chemical methods to optimise the structures of 50 PPCPs analogues, screened Dragon molecular structure descriptors based on factor analysis, and constructed a quantitative structure-activity relationship (QSAR) model for the reaction rate between PPCPs and ozone. The genetic algorithms-multivariate linear regression model was constructed and characterised according to the Organisation for Economic Cooperation and Development guidelines on QSAR model construction and validation. The results demonstrate that the model has good goodness of fit, robustness and good predictive ability. The application domain (AD) of the model, as defined by Williams plot, revealed the presence of one X outlier and two Y outliers. Consequently, the constructed QSAR model can be employed to predict the ozone reaction rate in other PPCPs wastewater within the application domain, thereby providing valuable insights for enhancing the removal process of PPCPs in wastewater treatment plants.