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Species persistence often depends not only on habitat protection, but also on habitat restoration. The effectiveness of species conservation through habitat restoration can be enhanced by explicitly considering ‘habitat availability’, the combined effects of the total amount of habitat and its spatial configuration. We develop an approach for prioritizing land for restoration in a complex biome, considering habitat availability, land acquisition cost and biogeographical representation in the Brazilian Atlantic Forest. We evaluate alternative restoration prioritization strategies for two mammal species with widely different dispersal abilities and habitat patch requirements. Our strategies focused on minimizing cost while meeting targets for biogeographical subregion representation and habitat availability metrics. We evaluated solutions based on the expected post‐restoration improvement in habitat availability per unit cost. Restoration through land acquisition to improve habitat availability for both species and to ensure 20% forest cover within each of the Atlantic Forest biogeographical subregions would cost US$ 17.5–20.5 billion. The 12.6 and 11.4 million ha of restored forest resulted in an increase of 10.5% and 9.8% in habitat area and 5518% (55‐fold) and 4100% (41‐fold) in future habitat availability for Leopardus pardalis and Caluromys philander, respectively. We found a high degree of concordance (> 75%) among selected planning units for each species. Substantial improvements in habitat availability that benefit both species can be realized for minimal additional cost relative to solutions based solely on cost‐minimization and biogeographical subregion representation. We demonstrate that metrics based on metapopulation theory can be quantified in complex systems and used in a systematic restoration prioritization approach to improve habitat availability cost‐effectively. Concordance among priority areas for restoration for species with widely different dispersal abilities and habitat patch requirements supports the idea that many species in the Brazilian Atlantic Forest might benefit from plans based on indicator species. This is particularly useful in data‐deficient systems like the Brazilian Atlantic Forest.