Evaluation of the diagnostic sensitivity (DSe) and specificity (DSp) of tests for infectious diseases in wild animals is challenging. The purpose of this review was to identify current gaps in test validation studies for infectious diseases in wild mammals. First, we conducted a systematic literature review of test validation studies for OIE-listed diseases in wild mammals published between 2008 and 2017. The review focuses on study design, statistical analysis, and reporting. Most published papers addressed Mycobacterium bovis infection in a one or more species of wild mammals. Our literature review revealed limitations or missing information about sampled animals, identification criteria for positive and negative samples, representativeness of source populations, species in the study, and information identifying animals sampled for calculations of DSe and DSp as naturally-infected captive, free-ranging, or experimentally-challenged animals. The deficiencies may have reflected omissions in reporting rather than design flaws, although lack of random sampling might have induced bias in estimates of DSe and DSp. Case studies of validation of tests for hemorrhagic diseases in deer and white-nose syndrome in hibernating bats were used to demonstrate approaches for validation when new viral serotypes or genotypes are detected and diagnostic algorithms are changed, and how tests evolve for a new disease after the causative agent has been identified. We describe potential benefits of experimental challenge studies for obtaining DSe and DSp estimates, methods to improve maintain sample quality, and Bayesian latent class models for statistical analysis. We make recommendations for improvements in future validation studies of diagnostic test accuracy in wild mammals.