The Göttingen minipig has been used as a surrogate in impact experiments designed to better understand the mechanisms by which mechanical loading induces traumatic brain injury (TBI). However, the relationship between mechanical response and structural morphology of the minipig cranium must be understood relative to the human skull in order to accurately scale any quantitative results, such as injury thresholds, from non-human TBI experiments to the human anatomy. In this study, bone specimens were dissected from the crania of adolescent Göttingen minipigs. These specimens were small cubes that contained the entire thickness of the skull. The microstructure of these skull specimens was quantified at the micron-length scale using micro-computed tomography (micro-CT). The skull was found to be highly porous near the skin-side surface and became less porous nearer the brain-side surface. The skull specimens were then loaded in quasi-static compression to obtain their mechanical response. The surface strain distribution on the specimen face was measured during loading using digital image correlation (DIC). The 2-D strain field formed a gradient of iso-strain bands along the thickness (depth) dimension from the skin-most to brain-most sides of the skull. The variation of the minipig microstructure along the thickness differed significantly from that of the adult human skull;​ thus the mechanical load transmission through the minipig skull is expected to be quite different from that of the human skull. The objective was to develop the methodology of relating the microstructure, as quantified by the bone volume fraction (BVF), to the mechanical response. The specimen was modeled by discretizing the depth dimension into a series of layers, which enabled the calibration of a power law relating the depth-dependent BVF to the depth-varying modulus. The relationship was used to predict moduli values for the adolescent minipig skull to provide updated, biofidelic parameters for finite element simulations at varying levels of complexity. Moreover, the methodology outlined in this paper can be applied to other skulls with different structural variations, such as the human.