Bone is a dynamic tissue whose remodeling throughout life is orchestrated by repeated cycles of destruction mediated by osteoclasts and rebuilding by osteoblasts. Current understanding of osteoclast biology has largely relied on the generation of knockout mice exhibiting an abnormal bone phenotype. This has provided a better understanding of osteoclast biology and the key proteins that support osteoclast function. However, mouse models alone do not provide an integrated view on protein networks and post-translational modifications that might be important for osteoclast function. During the past years, a number of MS-based quantitative methods have been developed to investigate the complexity of biological systems. This review will summarize how such approaches have contributed to the understanding of osteoclast differentiation and function.