Devising a model to figure out metaheuristics performances when applied to high demanding problems is paramount. Such a model would allow to foresee the computational time required for a given output quality. In previous works we showed that the performance of CHC and PBIL evolutive algorithms fit in a Gamma distribution when applied to solve the Root Identification Problem for search domains bounded by 2$20$ instances. Here we conduct experimental studies to verify that the Gamma model applies to search spaces of up to 2$^50$. Then we apply the model to estimate the runtime for search spaces of size up to 2$^100$. Finally we run the algorithms and validate the model by comparing the actual runtime values to those yielded by the model.