The analogues approach, developed by CCAFS in R programming, is a novel way of supporting climate and crop models with on-the-ground empirical testing. In essence, the analogues tool connects sites with statistically similar (‘analogous’) climates, across space (i.e. between locations) and/or time (i.e. with past or future climates). A CCAFS dissimilarity index or Hallegatte index can be used to systematically identify climate analogues across the world, for certain regions, or among specific locations. Users may use default criteria or choose from a variety of global climate models (GCMs), scenarios, and input data. Once analogue sites are identified, information gathered from local field studies or databases can be used and compared to provide data for further studies, propose high-potential adaptation pathways, facilitate farmer-to-farmer exchange of knowledge, validate computational models, test new technologies and/or techniques, or enable us to learn from history. Users may manipulate the tool in the free, open-source R software, or access a simplified user-friendly version online.