The current tools for geometric analysis of micro-electromechanical systems (MEMS) are primarily limited to those of the semiconductor industry. These tools are suited for measuring entities that are two-dimensional in nature such as lines, circles, and planes. Hardware that is capable of collecting three-dimensional data is typically limited by the slope variations in the surfaces of the part, and cannot accurately capture information from steep sidewalls, particularly in parts fabricated using the LIGA micro-fabrication process. This research develops a methodology to qualify MEMS, by implementing a novel computer-aided inspection (CAI) software framework. This software platform uses data acquired from current MEMS inspection hardware, and applies newly developed analysis algorithms to geometrically characterize a part. This work implements algorithms for all the procedures typical to a CAI program (e.g., point-to-entity assignment, registration, and data analysis) in addition to new techniques suited for inspection of high aspect ratio MEMS. This methodology describes possible registration errors based on the type of geometries being analyzed and the type of data acquired. Analyses of multiple point clouds with the use of fiducial information are shown to provide a critical link between single point cloud analyses that has heretofore been unrealized.