In the field of education, student learning progression is structured as a hierarchical organization, wherein lower grade levels are set to proceed to higher levels as their knowledge advances. However, their progression is stochastic in nature due to various reasons such as difficulty and number of units of courses. With this, the present study aims to develop a Markov Model to examine the flow of Industrial engineering students in a quarter system. The data used in this research were the enrolled subjects of Industrial engineering students of admission batch 2019 from the first term of their first year up to the third term of the second year, as well as their marks for the said courses. This scenario was modeled as an Absorbing Markov Chain. In the analysis, it was determined that if a student starts his first term in the university, it is expected that he spends an average of 15.5574 terms in the span of the seven terms. Also, if a student starts his first term, there is 29.40% chance that he withdraws and 70.59% that he proceeds. If he starts in the second term, there is 24.99% chance of withdrawing and 75.00% chance of progressing. For the remaining states, the chance of eventually reaching the fourth term of the second year is 100%. Lastly, based on their responses, their failure in courses was mostly due to problems like learning environment and lack of motivation, while they take lesser courses per term due to difficulties in handling multiple courses.