A novel time series analysis procedure is presented to localize damage sources in a mechanical system. An attempt is made to pinpoint the sources of nonlinear damage by solely analysing the vibration signatures recorded from a structure of interests. First, a linear prediction model, combining Auto-Regressive(AR) and Auto-Regressive with eXogenous inputs(ARX) techniques, is estimated using a time series recorded under an undamaged state of the structure. Then, the residual error, which is the difference between the actual time measurement and the prediction from the previously estimated AR-ARX combined model, is defined as our damage-sensitive feature. This study is based on the premise that if there were damage in the structure, the prediction model previously identified using the undamaged time history data would not be able to reproduce the newly obtained time sseries data measured under a damaged state of the structure. Furthermore, the increase of the residual errors would be maximised at the sensors instrumented near the actual damage locations. The applicability of this approach is demonstrated using the vibration test data obtained from an eight degrees-of-freedom(DOF) mass-spring system.