College course scheduling plays a pivotal role in a student’s development, academically and professionally. Schools without a standardized class scheduling system can generate many scheduling conflicts – some with the potential to seriously impact the student’s course progression, and thus delay their graduation dates. The optimization model proposed in this article can identify and eliminate those scheduling conflicts through the use of visual modeling and linear programming. Constraints for this model were taken from the individual department’s requirements and prerequisites, and instructor preferences, while allowing for the maximum number of available classes by minimizing and/or eliminating the number of class overlaps. An iterative process of analyzing and improving the schedule between visual modeling and linear programming enables the optimal result to be attained. This modeling system was applied to eight different semester schedules at an ABET-accredited university. The applied methodology yielded results of improved scheduling by an average of 83.46% over the original schedule, with a statistical confidence of 95.14%. By reducing the overall number of possible scheduling conflicts, it provides the students with more options and the ability to succeed. This type of class scheduling technique is not known to exist outside this study. The success rate of this technique far outstrips any success rate by any other documented method.