Animal models are essential for making the transition from scientific concepts to clinical application. Such models have proven valuable for spinal research. The cervical spine of sheep is often used because there is similar geometry between sheep and human. Although anatomical similarities are important, biomechanical correspondence is imperative to understand the effects of disorders, surgical techniques, and implant designs. Therefore, the purpose of this study was to conduct a comprehensive study of the sheep cervical spine biomechanics, including experimental and finite element analysis. To determine the flexibility of the multilevel spine, ten adult Suffolk sheep C2-C7 spines were tested, undergoing flexion-extension, lateral bending, and axial rotation. In addition to intact multilevel testing, the roles of the stabilizing structures were studied by sequentially destabilizing function spinal units. The sheep spine is highly flexible, especially in lateral bending (±65˚); motion increases with caudal progression. The sheep spine also has a large neutral zone accounting for 50-75% of the total motion. The facets and capsular ligaments play a key role in stabilization, providing the most stability at the C2-C3 level. In addition to flexibility testing, the sheep spinal ligaments underwent tensile testing until failure to determine the material properties. The ligamentum flavum has the largest failure stress and the capsular ligaments have the largest mean failure force. The longitudinal ligaments have the largest failure strain and the lowest failure force. Overall, the C2-C3 ligaments had the highest failure forces as compared to the ligament type at different levels. This corresponds to the stability the ligaments have at the C2-C3 level during flexibility testing. Moreover, a finite element model of the C2-C7 sheep cervical spine was developed and validated to provide additional insight in the sheep biomechanics. The model compared favorably with experimental testing for all loading cases except ACKNOWLEDGMENTS First and foremost, I want thank my advisor Dr. Nicole Grosland. It was with her encouragement that I pursued my doctorate. Her knowledge and advice has guided me and helped me grow as a researcher, student, and person. Without her patience and direction this would not have been possible. I would also like to thank my committee members for taking time out of their busy schedules. I am grateful for their input and suggestions. Their insights have led to further improvement of this research study.