This article summarizes a process which exemplifies the potential impact of municipal investment on the burden of cardiovascular disease (CVD) in city populations. We report on Developing an evidence-based approach to city public health planning and investment in Europe (DECiPHEr), a project part funded by the European Union. It had twin objectives: first, to develop and validate a vocational educational training package for policy makers and political decision takers; second, to use this opportunity to iterate a robust and user-friendly investment tool for maximizing the public health impact of ‘mainstream’ municipal policies, programs and investments. There were seven stages in the development process shared by an academic team from Sheffield Hallam University and partners from four cities drawn from the WHO European Healthy Cities Network. There were five iterations of the model resulting from this process. The initial focus was CVD as the biggest cause of death and disability in Europe. Our original prototype ‘cost offset’ model was confined to proximal determinants of CVD, utilizing modified ‘Framingham’ equations to estimate the impact of population level cardiovascular risk factor reduction on future demand for acute hospital admissions. The DECiPHEr iterations first extended the scope of the model to distal determinants and then focused progressively on practical interventions. Six key domains of local influence on population health were introduced into the model by the development process: education, housing, environment, public health, economy and security. Deploying a realist synthesis methodology, the model then connected distal with proximal determinants of CVD. Existing scientific evidence and cities’ experiential knowledge were ‘plugged-in’ or ‘triangulated’ to elaborate the causal pathways from domain interventions to public health impacts. A key product is an enhanced version of the cost offset model, named Sheffield Health Effectiveness Framework Tool, incorporating both proximal and distal determinants in estimating the cost benefits of domain interventions. A key message is that the insights of the policy community are essential in developing and then utilising such a predictive tool.