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Renewable energy from woody biomass, such as logging residues, has gained an increased interest because of its potential to reduce carbon dioxide (CO2) emissions and mitigate climate change. This study used a spatial logistic regression model to estimate the probability that mills in the southern United States will be willing to use additional logging residues based on their geographical location and proximity to existing transportation networks, other mills, forested areas, and city centers. Information on mill willingness to use logging residues was collected through a mail survey, whereas data on geospatial factors were obtained from public online databases. Mills were more likely to use additional logging residues if they were close to a major road; a sawmill; a pulp, paper, and paperboard mill; and a post mill. Mills close to a major river, a mill classified as producing other forest products, a forest, and a city center were less likely to use additional logging residues. Results will be helpful in identifying mills and outlying geographic locations best suited for electricity production using logging residues as well as prioritizing bioenergy investments.