In this article, the comparison among different techniques applied to simulation and representation of the expansion of the coffee berry borer in the Colombian coffee crops is carried out. First, a brief description of supervised techniques (models focused on data adjustment): Neural networks, neuro-fuzzy and fuzzy logic. Then, implementing these models is described. Finally, the comparison among these models is shown, highlighting performance of neuronal networks.