The article describes an application of collaborative decision analysis with a diverse team of stakeholders who preserve, manage, or restore tidal marshes across the San Francisco Bay estuary, USA, as a case study. A Bayesian decision network revealed that a strategy considering sea-level rise and storms explicitly in tidal-marsh restoration planning and designs was optimal, and it was robust to uncertainties about management effectiveness and budgets. The decision-analytic framework is sufficiently general to offer an adaptable template, which can be modified for use in other areas that include a diverse and engaged stakeholder group.