Two different methods are used to simulate the pulping process in a Kraft digestor - a deterministic model based on kinetic equations and mass transfer and a neural network model, based on a series of training patterns with usual process variables as inputs and pulp composition as output. The study indicates which process parameter have stronger influence on delignification rate, and shows that the neural network and the deterministic model present equivalent results.