A novel process monitoring method is proposed that uses predictions from a dynamic model to predict whether process variables will violate an emergency limit in the future. The predictions are based on a Kalman filter and disturbance estimation. A critical feature of the proposed method is the evaluation of a T-2 statistic as a "reality check" for deciding if the future predictions are reliable and thus can be used for making control decisions. Several simulation examples demonstrate the effectiveness of the proposed technique for both linear and nonlinear processes, and for a variety of disturbances. (C) 2001 Elsevier Science Ltd. All rights reserved.