Habitat destruction and fragmentation are principal causes of species loss. While a local population might go extinct, a metapopulation—populations inhabiting habitat patches connected by dispersal—can persist regionally by recolonizing empty patches. To assess metapopulation persistence, two widely adopted indicators in conservation management are metapopulation capacity and patch importance. However, we face a fundamental limitation in that assessing metapopulation persistence requires that we survey or sample all the patches in a landscape:" often these surveys are logistically challenging to conduct and repeat, which raises the question whether we can learn enough about the metapopulation persistence from an incomplete survey. Here, we provide a robust statistical approach to infer metapopulation capacity and patch importance by sampling a small proportion of all patches. We provided analytic arguments on why the metapopulation capacity and patch importance can be well predicted from sub samples of habitat patches. Full factorial simulations with more complex models corroborate our analytic predictions. We applied our model to an empirical metapopulation of mangrove hummingbirds (Amazilia boucardi). Based on our statistical framework, we provide some sampling suggestion for empirical studies of metapopulation capacity. Our approach allows for rapid and effective inference of metapopulation persistence from incomplete sampled data.