With the constant evolution of additive manufacturing (AM) processes, there is a need to adapt current characterization methods to better understand metallic powder behavior. Accurate and quantifiable characterization of powder particles is essential for qualification, certification, and quality control of AM manufactured parts. Particle morphology is often stated as an important parameter that affects powder flowability, layer density/uniformity, and—ultimately—part quality. However, work still needs to be accomplished to correlate particle characteristics to their impact on AM processes and manufactured parts. This study presents the sensitivity of various shape descriptors used in two-dimensional image analysis to particle morphologies commonly observed in AM. The objective was to determine which standard descriptors could adequately differentiate powder characteristic features such as elongation, facets, number, and size of satellites. To do so, a library of schematized particles containing various shapes was used and a sequential methodology capable of adequately classifying and quantifying particle shapes was developed. The methodology was then validated on metallographic cross sections of powders. The proposed approach could serve as a guide when selecting the most appropriate shape descriptors to monitor various powder characteristics and also provide a more complete characterization of particle morphologies.