The objective of metallurgical column control is to achieve the economic optimum combination of concentrate grade and mineral recovery for any given feed. Metal prices and the cost of consumables will dictate the metallurgical concentrate and mineral recovery targets. Furthermore, experience has shown that collection zone height, air holdup and bias water flow rare are key parameters (controlled variables) that affect metallurgical performance. The collection zone height is related mainly, with the residence time of the particles inside the collection zone, air holdup is correlated to the available surface area of air bubbles and bias water pow rare is an indirect measure of the cleaning action of the froth zone. However, these variables cannot be directly manipulated. Instead, wash water, air and underflow flowrates are the directly manipulated variables [1]. Therefore, if dynamic relationships could be established between the three manipulated variables and the three controlled variables, column metallurgical control may be improved. This study was an attempt to model these relationships using a tool known as System Identification, that includes Transient Analysis. The study consists in experimental tests, transient response analysis and identification of black box type models with cross validation. The experimental work was performed in a pilot scale laboratory flotation column of 3.2m high by 80mm of diameter. This flotation column operates in a plant with all the required instrumentation installed. The stud, considers the operation of the two phase air-water system.