The main aim of the paper is to monitor the micro- milling tool wearing process offline, by a microscopic tool measurement on one hand, and using high-frequency vibration measurement online, during the cutting process, on the other. Relations between the rake face wear stages and the measured online and offline parameters were determined applying an owndeveloped, artificial neural network based feature selection solution. As the main result, the experiment-based research appoints that the measured vibration variable component(s) which characterizes the key, three tool wearing phases, in the same way as the real rake face wearing stages occur, applying the waveform tool path