1. A computer-implemented method for model optimization, comprising: obtaining respective distribution descriptions of a plurality of input parameters to a model, the model indicating interrelationships between the input parameters and one or more output parameters of a system design; specifying respective search ranges for the plurality of input parameters; simulating the model to determine a desired set of input parameters within the search ranges based on a zeta statistic of the model; determining respective desired distributions of the input parameters based on the desired set of input parameters; determining significance levels of the input parameters in interacting with the output parameters based on the simulation and on the desired distributions of the input parameters, including: obtaining data records of the input parameters and the output parameters based on the simulation of the model; building a multiple layer tree diagram based on the data records, the tree diagram including a trunk node representing the data records, a plurality of split points, and a plurality of layer nodes, wherein each split point corresponds to one of the input parameters and the layer nodes are coupled to the trunk node via the split points; and determining the significance levels of the input parameters based on the order of the split points in relation to the trunk node; and identifying, based on the significance levels of the input parameters, a parameter of the system design that has a threshold design tolerance; presenting the determined significance levels, including: displaying a graphical representation of the tree diagram to a user via a display device; and outputting, via the graphical representation, a representation of the identified parameter of the system design that has the threshold design tolerance.