More often than not, the rolling element bearings in rotating machinery are the mechanical components that are first prone to premature failure. Early warning of an impending bearing failure is vital to the safety and reliability of high-speed turbomachinery. Presently, vibration monitoring is one of the most applied procedures in on-line damage and failure monitoring of rolling element bearings. This paper presents results from an experimental rotor-bearing test rig with quantified damage induced in the supporting rolling element bearings. Both good and damaged radial and tapered ball bearings are used in this study. The vibration signatures due to damage at the ball elements and the inner race of the bearing are also examined. Vibration signature analyzing schemes such as frequency domain analysis, and chaotic vibration analysis (modified Poincare diagrams) are applied and their effectiveness in pinpoint damage are compared in this study. The size/level of the damage is corroborated with the vibration amplitudes to provide quantification criteria for bearing progressive failure prediction. Based on the results from this study, it is shown that the use of the modified Poincare map, based on the relative carrier speed, can provide an effective way for identification and quantification of bearing damage in rolling element bearings.