The objective of this study was to understand the biomechanics in age-related primary traumatic brain injuries (TBI) causing initial severity and secondary progressive damage and to develop strategy reducing TBI outcome variability using biomechanical reconstruction to identify types of causal mechanisms prior to clinical trials of neuro-protective treatment. The methods included the explanation of TBI biomechanics and physiopathological mechanisms from dual perspectives of neurosurgery and biomechanical engineering. Scaling of tolerances for skull failure and brain injuries in infants, children and adults are developed. Diagnostic assumptions without biomechanical considerations are critiqued. Methods for retro- spective TBI reconstruction for prevention are summarized. Mechanisms of TBI are based on the differences between the mechanical properties of the head and neck related to age. Skull fracture levels correlate with increasing cranial bone thickness and in the development of the cranial sutures in infants and in adults. Head injury tolerance levels at three age categories for cerebral concussion, skull fracture and three grades of diffuse axonal injuries (DAI) are presented. Brain mass correlates inversely for TBI caused by angular head motions and locations of injurious stresses are predictable by centripetal theory. Improved quantitative diagnosis of TBI type and severity levels depend primarily on age and biomechanical mechanisms. Reconstruction of the biomechanics is feasible and enables quantitative stratification of TBI severity. Experimental treatment has succeeded in preventing progressive damage in animal TBI models. In humans this has failed, because the animal model received biomechanically controlled TBI and humans did not. Clinical similarities of human TBI patients do not necessarily predict equivalent biomechanics because such trauma can be produced in various ways. We recommend ‘reverse engineering’ for in-depth reconstruction of the TBI injury mechanism for qualitative diagnoses and reduction of outcome variability.