In recent time e-learning course are much demand subject. Student’s performance and predicting increasing with e-learning. So this paper covers the Decision Tree Approach for Predictive Analytics of student’s performance and it’s Big Data Implication. These systems are connecting many educational institutes to students overcoming the trivial limitations of location and time for studies. Big Data integration in E-learning system using data mining technique is also presented. They analyzed different types of data mining algorithms and use Decision tree algorithm in this paper. Decision Tree Algorithm for analyzing large students’ data was presented. Decision tree Integration with Map-Reduce Framework is proposed as compared to Traditional Decision Tree implementation. It will lead more efficient predictive analytics of student performance. It also identify the student risk of failing or dropping off from the course. So they proposed C4.5 Decision Tree methodology implementation in Big Data’s Map-Reduce framework for E learning Systems to better predict students’ performance.