In this paper we discuss how recently emerged machine learning approach, and conventional graph theoretic approaches used for the prediction of missing links in real world complex networks. Future projected plan can be build based on prediction results. This paper shows that the machine learning approach is significantly good as a newly emerged field. If any real-world situation can be mapped in to complex graph. where the nodes in the graph represent different objects of real world, and the links in the graph denotes the link, then a subset of these links is given as an input to the algorithm for prediction. It will also be describe the mechanism of different structural based link prediction algorithms. Keywords: Graph Theoretic Approach, Machine Learning, Complex Networks, Neural Networks, Link Prediction.