Abstract: Population based exhaustive replacement method(s) (PERM) for optimal variables selection and generation of regression models, to overcome conventional approaches, thereof is described herein. PERM initializes population based on one or more criteria, wherein one or more paths for variables/descriptors 1 to r for replacement with remaining descriptors wherein the one or more paths are updated based on relative error associated with each variable. For each combination of descriptors of r size, inter correlation of the descriptors are verified and predictive models are built. Subsets of variable with higher predictive ability are selected for substitution of initial population to obtain an updated population on which a replacement method is performed to obtain optimal set of variables. One or more variables of optimal set are randomly replaced, and perturbation can be performed on the top best subsets to converge at global optimum.