A vast number of applications do not have ample training data and consequently the accuracies suffer. There is a need to develop a technique to optimally and intelligently augment such datasets and design an automated classifier which gives good performance despite the smallness of dataset size. Meticulously stored data will ease retrieval. Artificial Immune System (AIS) is one amongst many computational algorithms in literature that are inspired by the dynamic learning mechanism of the human system. AIS based classification algorithm was proposed initially as one of the machine learning techniques which is suited for supervised learning problems. There are various applications areas of this powerful algorithm. We present a novel technique inspired by clonal selection to augment small datasets and classification.