The International Union for Conservation of Nature's (IUCN) Red List is the global standard for quantifying extinction risk but assessing population reduction (criterion A) of wide-ranging, long-lived marine taxa remains difficult and controversial. We show how Bayesian state–space models (BSSM), coupled with expert knowledge at IUCN Red List workshops, can combine regional abundance data into indices of global population change. To illustrate our approach, we provide examples of the process to assess four circumglobal sharks with differing temporal and spatial data-deficiency: Blue Shark (Prionace glauca), Shortfin Mako (Isurus oxyrinchus), Dusky Shark (Carcharhinus obscurus), and Great Hammerhead (Sphyrna mokarran). For each species, the BSSM provided global population change estimates over three generation lengths bounded by uncertainty levels in intuitive outputs, enabling informed decisions on the status of each species. Integrating similar analyses into future workshops would help conservation practitioners ensure robust, consistent, and transparent Red List assessments for other long-lived, wide-ranging species.