A method of modelling system behaviour of a physical system, the method including the following steps performed in one or more electronic processing devices: a) obtaining quantified system data measured for the physical system, wherein the physical system is an engine, pump, turbine, or motor, or their component parts, the quantified system data being at least partially indicative of the behaviour of the physical system for at least a time period, the quantified system data including measured attributes of the physical system obtained from sensor data received from sensors, wherein the sensors include at least one of position sensors, motion sensors and temperature sensors that collect data about the physical system behaviour; b) forming at least one population of model units, each model unit including model parameters and at least part of a model, the model parameters including coefficients that are derived from the quantified system data, each model including one or more mathematical equations for modelling the behaviour of the physical system; c) for each model unit: i) calculating at least one solution trajectory for at least part of the at least one time period; ii) calculating a fitness value based at least in part on the at least one solution trajectory; iii) iteratively modifying the model unit over a number of generations in accordance with the fitness value of each model unit by modifying at least one of: at least part of the model; and, the model parameters; and, d) selecting a combination of model units using the fitness values of each model unit, the combination of model units representing a collective model that models the system behaviour, wherein the modelling system uses a differential or difference equation model indicative of operation and interaction of individual components, together with the quantified system data, to develop a customised model specific to the particular equipment and its current behaviour, wherein the model includes model parameters corresponding to aspects of the system that cannot be practically measured and is used to at least one of: i) predict when failures are imminent; ii) to determine when the behaviour reaches or will reach a threshold condition; and, iii) to develop control processes to control operation of the equipment. a) obtaining quantified system data measured for the physical system, wherein the physical system is an engine, pump, turbine, or motor, or their component parts, the quantified system data being at least partially indicative of the behaviour of the physical system for at least a time period, the quantified system data including measured attributes of the physical system obtained from sensor data received from sensors, wherein the sensors include at least one of position sensors, motion sensors and temperature sensors that collect data about the physical system behaviour; b) forming at least one population of model units, each model unit including model parameters and at least part of a model, the model parameters including coefficients that are derived from the quantified system data, each model including one or more mathematical equations for modelling the behaviour of the physical system; c) for each model unit: i) calculating at least one solution trajectory for at least part of the at least one time period; ii) calculating a fitness value based at least in part on the at least one solution trajectory; iii) iteratively modifying the model unit over a number of generations in accordance with the fitness value of each model unit by modifying at least one of: at least part of the model; and, the model parameters; and, i) calculating at least one solution trajectory for at least part of the at least one time period; ii) calculating a fitness value based at least in part on the at least one solution trajectory; iii) iteratively modifying the model unit over a number of generations in accordance with the fitness value of each model unit by modifying at least one of: at least part of the model; and, the model parameters; and, at least part of the model; and, the model parameters; and, d) selecting a combination of model units using the fitness values of each model unit, the combination of model units representing a collective model that models the system behaviour, wherein the modelling system uses a differential or difference equation model indicative of operation and interaction of individual components, together with the quantified system data, to develop a customised model specific to the particular equipment and its current behaviour, wherein the model includes model parameters corresponding to aspects of the system that cannot be practically measured and is used to at least one of: i) predict when failures are imminent; ii) to determine when the behaviour reaches or will reach a threshold condition; and, iii) to develop control processes to control operation of the equipment. i) predict when failures are imminent; ii) to determine when the behaviour reaches or will reach a threshold condition; and, iii) to develop control processes to control operation of the equipment.