Assessing health outcomes associated with exposure to polychlorinated biphenyls (PCBs) is important given their persistent and ubiquitous nature. PCBs are classified as a Group 1 carcinogen, but the full range of potential noncancer health effects from exposure to PCBs has not been systematically summarized and evaluated. We used systematic review methods to identify and screen the literature using combined manual review and machine learning approaches. A protocol was developed that describes the literature search strategy and Populations, Exposures, Comparators, and Outcomes (PECO) criteria used to facilitate subsequent screening and categorization of literature into a systematic evidence map of PCB exposure and noncancer health endpoints across 15 organs/systems. A comprehensive literature search yielded 62,599 records. After electronic prioritization steps, 17,037 studies were manually screened at the title and abstract level. An additional 900 studies identified by experts or supplemental searches were also included. After full-text screening of 3889 references, 1586 studies met the PECO criteria. Relevant study details such as the endpoints assessed, exposure duration, and species were extracted into literature summary tables. This review compiles and organizes the human and mammalian studies from these tables into an evidence map for noncancer health endpoints and PCB mixture exposure to identify areas of robust research as well as areas of uncertainty that would benefit from future investigation. Summary data are available online as interactive visuals with downloadable metadata. Sufficient research is available to inform PCB hazard assessments for most organs/systems, but the amount of data to inform associations with specific endpoints differs. Furthermore, despite many years of research, sparse data exist for inhalation and dermal exposures, which are highly relevant human exposure routes. This evidence map provides a foundation for future systematic reviews and noncancer hazard assessments of PCB mixtures and for strategic planning of research to inform areas of greater uncertainty.