Biologists have developed a wide range of morphological, biochemical and physiological metrics to assess the health and, in particular, the energetic status of individual animals. These metrics originated to quantify aspects of human health, but have also proven useful to address questions in life history, ecology and resource management of game and commercial animals. We review the application of condition indices (CI) for conservation studies and focus on measures that quantify fat reserves, known to be critical for energetically challenging activities such as migration, reproduction and survival during periods of scarcity. Standard methods score fat content, or rely on a ratio of body mass rationalized by some measure of size, usually a linear dimension such as wing length or total body length. Higher numerical values of these indices are interpreted to mean an animal has greater energy reserves. Such CIs can provide predictive information about habitat quality and reproductive output, which in turn can help managers with conservation assessments and policies. We review the issues about the methods and metrics of measurement and describe the linkage of CIs to measures of body shape. Debates in the literature about the best statistical methods to use in computing and comparing CIs remain unresolved. Next, we comment on the diversity of methods used to measure body composition and the diversity of physiological models that compute body composition and CIs. The underlying physiological regulatory systems that govern the allocation of energy and nutrients among compartments and processes within the body are poorly understood, especially for field situations, and await basic data from additional laboratory studies and advanced measurement systems including telemetry. For now, standard physiological CIs can provide supporting evidence and mechanistic linkages for population studies that have traditionally been the focus of conservation biology. Physiologists can provide guidance for the field application of conditions indices with validation studies and development of new instruments.