In this work, a supervised machine learning (ML) multi-output regression approach is investigated to build predictive models for an industrial unit of phosphoric acid production. More specifically, multioutput data-driven applied simultaneously estimate nine outputs (Reactor temperature, chemical yield (RC), P 2 O 5 concentration in the acid, and losses gypsum) under different operating conditi...