Drill wear or breakage often damages the work piece and/or machine tool. Spindle motor current reflects the cutting process and the signal can be easily and inexpensively obtained. This paper presents a strategy for on-line drilling tool wear and breakage monitoring. It employs Wavelet Transform (WT) of the spindle current signature to perform monitoring. A moving window technique is used to extract the cutting portion of data from the entire data sequence. A low pass de-nosing filter is employed to remove noise from the current signal. Features were extracted using WT node energy and selected based on their ability to detect tool wear and chipping. The Progression of tool wear based on feature of WT detail level 4 is analyzed and pointed out status of worn or chipped tool. Experimental results validate performance of the proposed algorithm.