This paper presents a methodology for maintaining the operational validity of simulation models of observable systems in order to support operational decisions. In this methodology, real-time system data are continuously compared against simultaneous prediction intervals on selected responses constructed using the simulation model. The methodology is illustrated through using a case example of a simulation model of a flexible manufacturing system. Different invalidating discrepancies between the model and the system are investigated. Results indicate that using nontraditional responses may lead to a faster detection of invalidating changes, the speed of detection is a function of the scope of the change, and the model may evolve with the system and continue to be used to guard against random changes.