Higher Education of a country perform a significant role in our India to develop every sector as well as build the backbone of a nation by providing higher, Specialized and job oriented education to the young generation. At present, around 459 state University, and 56 central University in Indian government and University Grant Commission of India (UGC). Recently Indian Government and UGC have taken the biggest discussion to ensure the quality of education, organization criteria to create productive graduates, post graduates, and researchers. Student satisfaction is mostly biggest challenges for university, institute and colleges. Our work is solving this problem for java programing and WEKA to predict the result of a student satisfaction for administration, academic, and placement for five-year session (2017-2023). If student found not going to do well in the student traced administration, academic and placement satisfaction ratio for this college. Student our satisfaction ratio inters and vote the university, and college rating for NAAC grading. Higher education is the essential rights of our youth. Policies of higher education give performers and underperformers. Lots of studies are ongoing to evaluate policies and end products of higher education. In this work we have reviewed work and predicted the suggestions given by various authors. Machine learning play important role in analysis of data related to higher education. We have selected Random forest classification technique for our work. At last; we have set outcomes of our suggested work using machine learning technology.