The development of knowledge has become increasingly important since, in the modern world, knowledge is the main factor driving economic progress. The quality and accessibility of a country's educational system, especially in terms of higher education, is directly tied to growth. Higher education establishments are therefore essential sources of information and innovators. Easy access to higher education is essential for the creation, sharing, and subsequent use of information for the economy’s growth. The goal of this study is to identify the critical variables influencing students’ decisions while selecting a higher education institution. The study highlights the body of work based on three factors: review, focus, and constraints. It took into account the large number of available studies, but only a small number that are relevant to the task. It also sought to examine the most recent body of research on predictive analytics in higher education, since there has been a boom in studies in recent years that use machine learning to forecast important academic outcomes based on student data. This study emphasized the stages involved in creating predictive models, along with their drawbacks and difficulties within the educational system.