Abstract: The biochemical treatment of coking wastewater is a complex process, it is a challenge to accurately regulate chemical dosing to ensure stable effluent quality. In this study, an intelligent control model based on a back propagation neural network (BPNN) was proposed to achieve precise prediction of effluent quality and chemical dosage in the biochemical treatment process of coking wastewater. The results demonstrated that the coefficient of determination (R²) of the effluent quality prediction model reached 0.904. The R² values for the chemical dosage prediction models were 0.604, 0.798, and 0.809, respectively. Data preprocessing techniques, including data cleaning and feature selection, significantly enhanced the predictive performance of the models. Moreover, the dual-output model exhibited superior predictive accuracy compared to single-output models. This study provides a theoretical basis for the intelligent regulation of biochemical treatment processes and chemical dosing systems in the coking industry