This study describes the development and validation of a full human body finite element model created for use in crash injury biomechanics research as part of the Global Human Body Models Consortium (GHBMC) project. The geometry of the model is based on a protocol that leverages the strengths of three clinical scanning methods; computed tomography (CT), magnetic resonance imaging (MRI), and upright MRI (i.e. subject in seated position). The protocol was applied to a living male volunteer (26 years, height, 174.9 cm, and weight, 78.6 kg) who met extensive anthropometric and health criteria. Computer Aided Design (CAD) data were developed from the images, containing significant anatomical detail. A region-specific development approach was used, with five Body Region Centers of Expertise (COEs) focused on meshing and validation of the Head, Neck, Thorax, Abdomen, and Plex (Pelvis and Lower Extremity). The regional models were then integrated into a full body model. Mesh connections between neighboring body regions were assembled using techniques based on the geometry, element type, and anatomic purpose. This consisted of nodal connections for all 1-D beam and discrete element connections (e.g. ligamentous structures), 2D shells (e.g. the inferior vena cava to right atrium), and many 3D tetrahedral and hexahedral structures (e.g. soft tissue envelope connections between body regions). In cases where node-to-node connections were not made, (e.g. 3D muscle to bone insertions), contact definitions were implemented. The integrated full body model consists of 1.3 million nodes, and 1.9 million elements. Element types in the model are 41.0 % hexahedral, 33.8 % tetrahedral, 19.5 % quad shell, 5.1% tri shell, and 0.6 % others including beam and discrete elements. Non-linear and/or viscoelastic material models were used where appropriate. Simulations were conducted using LS-DYNA MPP971 R.4.2.1. The model has been validated against a number of frontal and lateral rigid impactor and sled tests. Two of these validation cases are highlighted in this work, displaying the model kinematics and kinetics. Through the use of a living subject, comprehensive image data, and extensive geometric validation, this model has the potential to provide a greater degree of accuracy in blunt trauma simulations than existing human body models. It will serve as the foundation of a global effort to develop a family of next-generation computational human body models for injury prediction and prevention.