Recently facial based age estimation has become increasingly important because of many potential real time applications. Age estimation is predicting someone's age by analyzing his/her biometric trait such as bone density, dental structure or face. Amongst these face is important trait so facial based age estimation has become more popular due to its vast real time applications. Age estimation is defined as to label the face image automatically with the exact age or age group. Estimating age from images has been one of the most challenging problems within the field of facial analysis due to uncontrollable nature of the aging process, high variance of observations within the same age range, lighting, facial expressions, pose, occlusion, blur, camouflage due to beards, moustache, glasses, makeup and the difficulty to gather complete and sufficient training data. This paper presents analysis of earlier techniques proposed by researchers for facial based age estimation. Different feature extraction and estimator learning methods used in this domain are also discussed. © 2017 IEEE.