Rapid prediction of the removal efficiency and energy consumption of organic contaminants under various operating conditions is crucial for advanced oxidation processes (AOPs) in industrial application. In this study, 1H-Benzotriazole (BTZ, CAS: 95-14-7) is selected as a model micropollutant, a validated incorporated Computational Fluid Dynamics (CFD) model is employed to comprehensively investigate the impacts of initial concentrations of H2O2, BTZ and dissolved organic carbon (DOC) (i.e., [DOC]0, [BTZ]0 and [DOC]0), as well as the effective UV lamp power P and volumetric flow rate Qv. Generally, the operation performance depends on [DOC]0 and [BTZ]0 in similar trends, but with quantitatively different ways. The increase in [H2O2]0 and P/Qv can promote •OH generation, leading to the elimination of BTZ. It is worth noting that P/Qv is found to be linearly correlated with the removal order of BTZ (ROBTZ) under specific conditions. Based on this finding, the degradation of other potential organic contaminants with a wide range of rate constants by UV/H2O2 is further investigated. A model for predicting energy consumption for target removal rates of organic pollutants is established from massive simulation data for the first time. Additionally, a handy Matlab app is first developed for convenient application in water treatment. This work proposes a new operable solution for fast predicting operation performance and energy consumption for the removal of organic contaminants in industrial applications of advanced oxidation processes.