This application relates to apparatus and methods for generating, and executing, surrogate models. In some examples, a computing device generates and evaluates correlations between input and output variables for a system to identify highly correlated input and output parameters. In addition, weights for one or more of the parameters may be determined. The computing device identifies a mathematical relationship between input and output variables to generate a physics model. The computing device may also identify other features not captured by the physical relationship that are highly correlated to each other, and generates a feature model that is based on the highly correlated features. The computing device may optimize the feature model based on a culling process that reduces the computational resources required to execute the feature model. The physics model is then combined with the feature model to generate a system output model that can simulate the system.