In this work, we present a hybrid methodology based on the ADA methodology, applied to the simulation of pine species from northern Mexico. From algebraic transformations and certain premises, we were able to reduce the parameter space of the Weibull growth function from 3 parameters to just 1, the maximum diameter of the individual at the end of growth. From the point of view of complexity, we have a decrease in computational cost, because now we have only one parameter to estimate, and from a practical point of view, it is an easy parameter to obtain, even in the field. To present the quality of the method, we used the mean absolute percentage error and the quantile regression to visually present the quality of the fit. Then we compare this proposed methodology with the GADA versions for the Chapman-Richards and Hossfeld models. The results presented for the study area, to avoid generalizations, show that the proposed hybrid method was more accurate in the estimates.