In this work, a model-based control strategy is presented for the Kappa number profile control of a continuous pulp digester. The strategy employs an empirically derived process model using subspace identification techniques. A state-space model predictive control algorithm is used to adjust five manipulated inputs in order to regulate five process outputs, in response to five randomly varying process disturbances (of which three are measurable:). Profile sensitivity to closed-loop response is also explored.