This study aims to clarify the statistical causal relationship between the locations of urban facilities and forecasted population changes according to types of residential clusters in the Osaka Metropolitan Fringe areas. This paper’s background is the location optimization plan policy formulated by the Japanese MLIT (Ministry of Land, Infrastructure, Transport, and Tourism) in 2015. The methods combined urban ecological analysis, cohort analysis, and Bayesian network analysis. Using the Bayesian network analysis, the causal relationship between the forecasted population change ratio and the urban facility location was analyzed. The results suggest the location of urban facilities for each residential cluster that will prevent a rapid population decline in the future. Specifically, in the sprawl cluster, this study found that residential areas closer to medical facilities will sustain the future population, while in the old new-town cluster, this study found that residential areas closer to train stations will best sustain the future population. However, in the public housing cluster, residential areas more distant from regional resources will best sustain the future population. Therefore, it is worth considering different urban designs in the old new-town and public housing clusters, rather than the location optimization plan policy.