Model-based gear dynamic analysis and simulation has been a promising way for developing effective gearbox vibration monitoring approaches. In this paper, based on the dynamic model of a one-stage gearbox with spur gears and one tooth crack, we investigate statistical indicators and the discrete wavelet transform (DWT) technique to identify effective and sensitive health indicators for reflecting the crack propagation level. Our results suggest that the root mean square (RMS) indicator is a good statistical indicator to reflect the crack propagation in the early stage; DWT can improve the sensitivity of the RMS indicator and the RMS indicator becomes more sensitive with the increase of the DWT level.