The efficiency of reverse flotation in iron ore beneficiation is highly dependent on hydrodynamic parameters that govern stability, selectivity, and metallurgical performance. Building on insights from comparative evaluations of self-aerated and forced-air mechanical flotation cells, this study explores how hydrodynamic indicators can be integrated into process control strategies to enhance iron ore production. Real-time monitoring of parameters such as air flow rate, bubble size, and velocity distribution can provides valuable feedback for optimising reagent dosage, froth depth, and air control systems. These parameters directly affect concentrate grade, tailings recovery, and energy consumption—key variables in automated process control. By linking hydrodynamic behaviour to operational data, predictive control algorithms can be developed to stabilise recovery and improve process efficiency. The integration of such feedback-driven control strategies represents a step toward smarter, data-informed iron ore flotation circuits with higher selectivity and reduced operational variability.