Net electricity consumption use continues to be a significant issue. There are various forms of energy use and production. This work uses a robust form of M-estimation by using the grid-search algorithm. Thus, since we use the form of Huber M-estimation, the prediction performance can be increased; because the data is tried to be modeled by using the different values of tuning parameter determined by the grid-search which can be used to carry out the optimization proving the Mestimates of the parameters of a regression model. The data sets which are a year and the net electricity consumption are modeled by a regression model in order to predict and forecast how much electricity consumption will be necessary for the commercial purpose firm used the electricity at the highest amount. The statistical inference for the regression model and its estimators of parameters in the model is also provided. Further, the illustrative results used for the grid search and the analytical expression of the regression model are given. Due to the fact that polynomial regression showing an increment in the polynomial trend can model the dependent variable well, the net electrical consumption in commerce at Turkiye increases, and the bandwidths for the forecasting in the years 2021 and 2022 are given to conduct planning in the energy sector.