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Despite global projections of increasingly concentrated urban population growth, many cities still suffer from severe depopulation (or shrinkage), which results in increased vacant land/structural abandonment. As a consequence, shrinking urban areas are now seeking ways to more intelligently inventory and manage declining neighborhoods. Smart Shrinkage, a means of planning for fewer people and less development, has become a popular approach to managing depopulation. This research explores current approaches to managing vacant urban land through case evaluations approach, using findings to inform an applied Smart Shrinkage strategy for repurposing vacant lots. Land use prediction modeling is integrated into the process using Dayton, Ohio, USA, as an application site. A GIS-based development suitability model was used to identify pockets of future nodal development, and the land transformation model (LTM) was used to predict areas of future decline. Typologies of vacant/abandoned lots were then developed based on spatial characteristics of each parcel. The result of the process is a framework for executing Smarter Shrinkage—a community-scaled approach integrating land use prediction modeling into the process for managing vacant lots. Findings suggest that forecasts from the LTM require policy mechanisms to be put into place that will allow land to be transformed for nonresidential uses that are consistent with where demand exists. Smarter Shrinkage approaches should emphasize the implementation of newly proposed development only within nodes of high development potential and should utilize temporary or green infrastructure-based functions in areas predicted to become vacant or with low development potential.