This investigation approaches the artificial neural networks applied to the pulp sedimentation process in carbonate-ammonia leaching. To carry out this research, the main variables that characterize the process were identified. Besides, it was collected the data that comprise a whole month of facility's operation. Furthermore, it was developed a regression analysis backwards, step by step, which allowed to determine that the linear correlation coefficient did not reach values higher than 0,7. In addition, it was pinpointed a two layered feed - forward back propagation neural network to model the pulp density. Thins one reached the correlation coefficient values of 0,91 during its training and validation, as well as 0,67 in its generalization.