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Estimating WRF model computation time is necessary because of the need for domain expansion for weather prediction. However, the optimum computation time is not simply gained by enlarging the domain and adding processor numbers. Thus, an investigation was carried out to determine the correlation between computation time on domain size, number of grids, and number of processors used to run the WRF model. This study uses a collection of computation time as the data input from running the WRF model with two domain group ratios, 2: 1 and 1: 1, and various processors. Negative Exponential Function (NEF) and Power Function (PF) as exponential decay functions are evaluated to represent the curve formed from the computation time against the number of processors in one domain case. This study also evaluates the speed up and efficiency of the use of processor numbers against the tested domains. NEF represents the decrease in computation time curve in a domain case better than PF since this function has a steeper slope, better initial value, and k constant that keeps the computation time falling below 0. The computation time can be optimally saved by adding approximately eight processors at the same domain ratio with four times larger grid size and the same amount of grid number. Investigations for other domain ratios need to be carried out to determine the characteristics of computation time on the number of processors, grid size, and domain size.