Pain, pretended to be the quinary decisive presage is an objective sensation instead of subjective and is extensively accepted in health care. The discernible vagaries reflected on the face of a person in pain are for a sparse seconds and comes naturally. To track this is a mysterious and time excruciating process in a clinical framework. This is the reason it is boosting scientists and specialists from medicinal, brain research and PC fields an interdisciplinary research and to emerge with something concrete for the gregarious cause. A useful measure of detecting pain intensity in a clinical framework is obtained by self-report. This technique has limitations as it is based on the subject perception and knowledge and provides no actual timing information. An endeavour has been made to code pain as a progression of facial action units (AUs) that can accomplish a target measure of pain. Utilizing FACS and acquiring self-governing datasets the system’s execution is tried for ground truth. The proposed strategy compares the previous class approaches like SVM and ANFIS in pain classification on the UNBC-McMaster shoulder pain expression database.