Dynamic simulations of gears and rolling element bearings have previously been made separately, but cases have been experienced in practice where bearing faults show up only because they modulate the gearmesh signal in a way that is different from the effects of gear faults. A combined gear/bearing model has been made to obtain a better understanding of the interaction of the two components. Results have previously been published for simulated local faults in the bearings. The simulation model has now been modified to model extended faults of the type that do not necessarily produce high frequency impact responses, but do modulate the gearmesh signals. This simulation model will be useful to test new diagnostic algorithms, as well as prognostic algorithms by varying the size of the simulated faults. A third application is to use the simulated signals to train neural networks to recognize the various faults without having to experience large numbers of failures. The paper compares simulated and actual signals (localized and extended inner race faults) from a gear/bearing test rig, and in particular demonstrates that they react similarly to existing diagnostic techniques.