Restoration efforts to increase wildlife habitat quality in agricultural landscapes have limited funding and are typically done on a first come, first serve basis. In order to increase the efficiency of these restoration efforts, a prioritized ranking system is needed to obtain the greatest increase in habitat quality possible for the fewest amount of hectares restored. This project examines the use of a GIS based multi-criteria approach to prioritize lands for reforestation along the Kaskaskia River in Illinois. Loss of forested area and corresponding increase in forest fragmentation has decreased songbird habitat quality across the Midwestern United States. We prioritized areas for reforestation based on nine landscape metrics: available agricultural land, forest cover gaps, edge density, proximity to river, 200 m corridor area, total forest core area, fringe core area, distance to primary core value, and primary core area. The multi-criteria analysis revealed that high priority areas for reforestation were most likely to be close to the riparian corridor and existing large blocks of forest. Analysis of simulated reforestation (0, 0.5, 1.0, 5.0 10.0, 25.0, and 50.0% of highest priority parcels reforested) revealed different responses for multiple landscape metrics used to quantify forest fragmentation following reforestation, but indicated that the study area would get the greatest rate of return on reforestation efforts by reforesting 10.0% of the highest priority areas. This project demonstrates how GIS and a multi-criteria analysis approach can be used to increase the efficiency of restoration projects. This approach should be considered by land managers when attempting to identify the location and quantity of area for restoration within a landscape.