Monitoring and controlling of metal cutting processes is an essential task in any modern precision machining setup. The implementation of proper monitoring process leads to promising results in terms of cutting tool life, machining costs, and production rates. Several techniques have been used to detect, monitor, and analyze different parameters associated with the cutting processes such as cutting tool wear, chip breakage and fracture, chatter vibrations, and formation of built-up edge (BUE). In this work, a review study is presented to discuss the research activities using the acoustic emission (AE) signals to monitor and control various machining processes. The discussed work does not only present an investigation of the AE signals, measured variables, and AE sensor setup during machining processes, but also shows several methods used for analyzing and processing the AE signals. The work focuses on studies, which employed AE in monitoring, and analyzing some specific characteristics such as chip formation and morphology, surface quality, and tool wear evolution for different machining operations and materials.