Cold spray, or supersonic particle deposition, is an emerging additive manufacturing process used to develop material on target substrates. The process continues to evolve toward full-fledged, metal 3D-printing applications. As these developments are made, there is a growing need for non-destructive process monitoring. Cold spray is dictated by numerous process parameters. Process consistency is vital for the development of highstrength coatings with predictable and repeatable microstructural, thermo-mechanical, and 3D printing properties (e.g., predictable shape). Detection of unexpected parameter variations, anomalous events, and spray failures is critical for identifying process inconsistencies, minimizing machine downtime, and maximizing cost efficiency. In this study, airborne acoustic (i.e., aero-acoustic) emissions were monitored during the cold spray process to examine acoustically detectable spray parameters. Characteristics of aero-acoustic waves that emanate from free and impinging supersonic jets were investigated. The viability of using these characteristics as real-time metrics for cold spray additive manufacturing applications was explored. Results showed that changes in nozzle gas supply pressure, nozzle gas inlet temperature, and main gas flow rate were detectable in free-jet experiments via frequency spectrum analyses. The influence of robotic arm motion and coating buildup on airborne acoustic signal trends was evaluated during cold spray deposition procedures. Band power and other signal features were extracted from recorded audio signals to compare temporal behavior. During deposition experiments, powder feeding rate (PFR) and standoff distance (SOD) variations were identified by acoustic characteristics. Nozzle wear experiments revealed the aero-acoustic detectability of nozzle wear conditions and rates. Delamination failures during spray procedures were identified in comparisons between normal and anomalous cases. An alarm program was developed for delamination detection through the acoustic monitoring of multiple frequency ranges. Audio signal analyses indicated the feasibility of acoustic event detection as a real-time process monitoring technique for the cold spray process.