Three-dimensional (3D) Gamma Compression Gamut Mapping Algorithm (GMA) is proposed in this study. Currently Gamma-Compression GMA has been designed to work in two-dimensional (2D) Lightness–Chroma planes segmented by primary and secondary hue regions. The advanced 3D GMA is expected to work in 3D uniform color space without color segmentation. This article describes the 3D GMA based on the concept of Image-to-Device (I-D). Considering color gamut relationships between source image and printer device, the Gamma-Compression GMA is applied to the 3D shell shapes in CIE L^*a^*b^* space. 3D gamut shells of a source image and printer device are formed by connecting the surface points located at their gamut surfaces. The surface polygon meshes or parametric cubic surfaces are built up from these most outside color points, and true seamless 3D mapping is performed. It is shown that the GMA coupled with 3D gamut compression and multimapping directions resulted in the better rendition than 2D nonlinear GMAs. It is also shown that 3D Gamma-Compression GMA works better than two known 3D GMAs, CARISMA and minimum ΔE₉₄ clipping. Two kinds of focal point decision rules, Image Lightness Division (ILD) and Focal Lightness Scaling (FLS), are introduced to find the optimum multimapping directions.