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Many signature analysis techniques have been developed for detecting bearing damage. In this paper, a number of these techniques are evaluated and their abilities to detect and trend damage are compared quantitatively. Needle bearings are used for this evaluation because they are noisier than ball bearings, and there has been little published regarding their vibration behavior. The signature analysis techniques are evaluated using three increasing levels of outer race damage. The evaluation criteria are based on the ability of a technique to repeatedly detect a damaged bearing and to correctly trend the damage progression. Results show that a number of time and frequency domain techniques correctly identify and trend the bearing damage. Of these techniques, the matched-filter root-mean-square (Mfrms) technique applied to an enveloped (smoothened) signal consisently showed high sensitivity to bearing damage and its progression.