Wear debris is produced in all machines containing moving parts. Wear debris or particles separate from these moving parts because of close contacts and friction and are contained in oil in an oil-wetted system. Analysis of wear debris provides important information about the condition of a machine. The produced particles come in different shapes, sizes, colors, and surface texture. This paper describes the morphological analysis of wear particles by using computer vision and image processing techniques. The aim is to classify these particles according to their shape attributes. Four particle shapes are classified by using Histogram of Oriented Gradients (HOG) and shape attributes including eccentricity, extent, major and minor axis length, equiv-diameter, and centroid distance. The shape classification can be used to identify origin of particle generation and thus predict wear failure modes in engines and other machinery. The objective of particle classification obviates reliance on visual inspection techniques and the need for specialists in the field.