This paper presents an objective somatotyping method based upon a three-dimensional Fourier descriptor (FD3) as an invariant body shape descriptor. Human body shape was assumed as a stack of cross-sectional contours, and shape features were extracted based upon the FD3. The FD3 represents the shape features on the spatial frequency domain. Because global shape features are concentrated on the lower frequency terms, it is possible to classify the body shape efficiently. Trunks of forty-eight male subjects were measured using laser range finding and image processing techniques, and FD3s were calculated from their trunk contours and classified using a hierarchical clustering algorithm using Euclidian distance metric. Clustering results were compared with the classical somatotyping and showed good correlation with visual classification.