Student loan debt and institutional student loan cohort default rates (CDR) have been one of the main topics of interest in colleges and universities in the most recent years and the impact of CDR's have played a major role in the strategic planning efforts by higher education administrators. The costs for tuition, fees, room and board for full-time students have steadily increased over the last decade, while state and federal support provided to universities has declined. This has forced universities to pass the increased financial burden to students in the form of increased tuition and fees. With the total tuition and fees at colleges and universities continuing to rise more rapidly than the rate of inflation, the need for federal student loans have continued to increase. In the fiscal year 2013, student's borrowed nearly $106 billion through the Federal Direct Loan programs, reaching the aggregate student loan debt of $1.2 trillion (Consumer Financial Protection Bureau, as cited in Webber & Rogers, 2014). Students who fail to make payments on their federal student loans for 270 consecutive day enter into default. As outlined by federal regulations, the consequences of defaulting on student loans include, but not limited to, garnishment of wages and Social Security benefit payments, ineligibility for additional federal student aid, and damages to credit history. Although, the federal government has established various methods to reduce the likelihood or prevent students from entering into default, such as in-school deferments, forbearance, and undue hardship petitions, student loan default rates have nearly doubled over the past decade as a growing number of students are unable to pay for the college education. As default rates begin to climb to over 20 percent in the mid-1980, policy makers became increasingly concerned that additional regulations were needed to control student loan default. The purpose of this study was to examine the relationship and predictability of the demographic, academic, and loan related factors that contribute the student loan default status at a historically black college in the Southern region of Texas. Student loan default prevention is an important goal for all institutions. The intent of this study was to help reduce or prevent future student loan default by identifying possible ways that an institution can intervene while students are still enrolled at the undergraduate level. This study was exploratory and quantitative in nature. Logistic regression analysis was used to determine the statistical relationship in predicting student loan default. Age, gender, ethnicity and parental income were all found to be significant predictors of student loan default. In addition, grade point average (GPA) was a significant predictor of student loan default and the students' educational status was found to be the strongest academically related predictors of student loan default. This researcher also revealed that the amount of loans borrowed were a significant predictor of student loan default. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]