Debt for public colleges and universities has been increasing while financial resources, which provide the support to repay debt, have been declining. As debt increases in proportion to assets, the risk profile of a college or university increases. This study examined the relationships between financial variables and institutional characteristics that relate to long-term debt and leverage of U.S. four-year public colleges and universities during a period of economic downturn. Understanding these relationships is needed to determine factors that enable or constrain public higher education's ability to borrow funds to meet organizational goals. In addition, this study also explored long-term debt and leverage trends categorized by Carnegie classification and geographic region from 2005 to 2009. The data for the study were obtained from IPEDS. Descriptive statistics, ANOVA, and OLS regression were used to analyze the data. The findings showed that both long-term debt and leverage of public institutions had increased from 2005 to 2009. However, leverage increased at a slower pace, which indicated that public universities were able to use existing assets to offset the increase in liabilities associated with the additional long-term debt. This study also found that differences existed in long-term debt by Carnegie classification. Doctoral/Research institutions had more long-term debt than Master's institutions, and Master's institutions had more long-term debt than Baccalaureate institutions. Although Master's institutions did not have the greatest amount of long-term debt, they had greater amounts of leverage than Doctoral/Research and Baccalaureate institutions in all fiscal years. Additionally, Master's and Doctoral/Research institutions located in the Northeast had mean leverage in all five years that exceeded recommended thresholds. The variable with the strongest relationship with long-term debt was property, plant, and equipment. Approximately 65.9% of the variance in long-term debt was explained by property, plant, and equipment. In comparison, the leverage model showed that geographic regions had the strongest relationship with leverage. Collectively, the West, Midwest, and Southeast regions accounted for 27.1% of the variance in leverage. The detailed results of the findings, conclusions, and recommendations are provided at the end of the study.