Ore floatability is defined as the propensity of particles to float within a flotation environment and any effective mathematical model of the flotation process must incorporate its effect. The objective of this thesis was to review the ore floatability models in the literature and for those considered appropriate: • investigate their basic assumptions, • evaluate the type of experimental data required to derive model parameters, • and test their predictive capability. A review of the literature identified three different methods of representing ore floatability in flotation circuit models. Two approaches were studied within this thesis, namely the empirically derived floatability component model and the property based floatability component model. The third shaped distribution modelling approach was considered too inflexible a methodology to represent all types of ore floatability distributions. Ore floatability cannot be directly measured but must be inferred from a flotation response. In this thesis, it was investigated using batch laboratory flotation tests which, for a particular system, were all performed using the same set of operating conditions. Any difference in response between tests performed in this way was attributed to a change in ore floatability. Within this thesis, hundreds of batch laboratory flotation tests were performed using samples collected from the streams of seven different industrial flotation circuits. These tests, in combination with circuit survey data, were used to investigate various assumptions underpinning the ore floatability models. The tests also provide the experimental information required to derive the flotation properties of the two chosen ore floatability models. Both the two models investigated in this thesis assume the floatability of a particle in a flotation circuit to remain the same before and after processes in the circuit. A nodal analysis technique was developed by the author to compare the floatability in the feed and product of a flotation circuit process using batch laboratory flotation test information. This technique was used to show that ore floatability is a conserved property across most flotation, mixing and cycloning processes. In the cases where floatability was not conserved, it is suspected that the surfaces of the particles have changed due to oxidation, adsorption of hydrophilic species or decomposition of reagent surface species. Ore floatability was usually not conserved across processes which are designed to change particle properties (e.g. reagent addition and regrinding). An additional requirement of the ore floatability models is that all particles assigned to a particular component must float with a similar flotation rate. Sizing and liberation analysis of batch laboratory flotation test data showed that property based floatability component models based on size and liberation alone do not satisfy this criteria. It was concluded that a property based model would need to include information about the chemical state of the particle surfaces. As this type of measurement was considered beyond the scope of this thesis, no further analysis of this type of model was possible. Techniques for determining the empirically derived floatability component model parameters were studied using statistical techniques. This analysis showed that unique, stable parameters could be obtained by fitting the models to match multiple batch flotation test data collected at the same time as a circuit survey. It was found that a minimum of four batch laboratory flotation tests were required to derive statistically stable parameters. The use of one laboratory batch flotation test (the traditional method of parameter derivation) results in parameters which are highly sensitive to the error in the batch laboratory flotation test data. A methodology to simulate and predict ore grade and recovery in a flotation circuit based on different ore floatability particle groupings was developed by the author. A theoretical analysis was performed using this algorithm which showed that a two floating component and one non-floating component model produced similar predictions to a multi-component model developed using size and liberation information in a circuit subject to changes in cell operation, residence time and circuit configuration. It was therefore concluded that a discrete floatability component model has the ability to represent, what is in reality, a more complex particle floatability distribution. The analysis performed in this thesis shows that the empirically derived ore floatability component model is a valid method of representing ore floatability within a flotation circuit model which does not contain grinding or reagent addition processes. Parameters of the model can be derived with statistical confidence using multiple batch flotation test data. To effectively model ore floatability in circuits containing regrinding or staged reagent addition, ore floatability models need to be developed which incorporate parameters related to the physical properties of the ore. It is therefore recommended that research be performed to determine the effect of size, liberation and chemical conditioning on the ore floatability of a particle and how these effects are best incorporated into an ore floatability model.