This study used quantitative hierarchical regression modeling to investigate factors influencing student grades in the context of online tutoring, guided by Tinto's persistence theory. The purpose of this quantitative predictive correlational study was to determine if and to what extent do demographics (gender and age), prior academic success (current programmatic GPA, accepted with specifications, transfer credits), tutoring (number of tutoring sessions in current course and week that tutoring was requested) predict students' final grade in an online undergraduate course at a university in the southwestern United States. The increasing prevalence of online education and the pivotal role of student-tutor interactions required a exploration of the predictors that contribute to academic success. The study utilized a sample of students in online tutoring, aiming to identify the hierarchical impact of various predictors on student grades. Block 3 produced the most predictive model (R[superscript 2] = 0.08, [delta]R[superscript 2] = 0.02, F = 3.74, p = 0.025). The analysis revealed that GPA prior to tutoring predicted the final grade ([beta] = 2.99, t(413) = 2.87, p = 0.004). On average, a one-unit increase in GPA prior to tutoring resulted in a 2.99-unit increase in the final grade. Transfer credits also predicted the final grade ([beta] = 0.15, t(413) = 2.53, p = 0.012). On average, a one-unit increase in transfer credits led to a 0.15 unit increase in the final grade. The week in which tutoring was sought was the most significant predictor to final grade by 1.82% per week ([beta] = -1.82, t(413) = -2.73, p = 0.007). This study had practical implications for educators, online tutoring platforms, and institutions seeking to enhance student success in virtual learning environments. Future research should explore additional factors to add persistence to the model. [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.]