This guide provides practical direction for designing impact evaluations that generate evidence useful for large-scale policy and program decisions. Many interventions that succeed in pilots lose effectiveness when expanded, in part because evaluations do not reflect who will be reached at scale, how programs will actually be delivered, or how spillovers may shape outcomes.  The guide outlines how teams can incorporate scalability and generalizability into evaluation planning—from identifying core components, selecting representative populations and settings, and building scalable monitoring systems, to anticipating cost dynamics and accounting for indirect effects. It offers a concise checklist and practical  guidance for researchers, implementers, and funders. By treating evaluations as the first stage of scale-up rather than isolated studies, this guide supports the generation of evidence that not only shows what works, but also whether it can work at scale.