A quantitative evaluation method based on a three-dimensional (3D) laser-scanning technique is presented for the objective assessment of fabric fuzziness. Fabric fuzziness, referring to severity of protruding fibers on a fabric surface, has a direct effect on fabric serviceability and needs to be evaluated routinely for quality assurance. In this research, the characterization of fabric fuzziness was realized by using a customized laser scanning system that can produce the 3D surface image of a fabric in a high resolution, and by analyzing the parameters of roughness amplitude distributions extracted from the 3D image. Multi-colored fabrics with different levels of fuzziness were first visually evaluated to obtain the subjective fuzziness grades in reference to a set of expert-rated cotton samples. Then, the fabrics were scanned by the laser system and the surface roughness parameters were calculated from the 3D images for the regression analysis with the subjective fuzziness grades. The result of multivariable regression analysis indicated that the fuzziness grade has a strong correlation with the roughness parameters, and can be estimated automatically after a fabric is scanned. The system demonstrated its fuzziness ratings are invariant to fabrics’ colors, prints, and structures.