The exact distinction of malignant leukocytes at minimal expenses during earlier phase of illness, which is a significant difficulty in disease diagnosis, is a real concern in the field of disease detection. Flow cytometry equipment is few, and the procedures available at laboratory diagnosis institutes are timeconsuming, despite the high frequency of leukaemia. The current systematic review was undertaken to examine the works aimed at discovering and classifying leukaemia using machine learning, which was motivated by the possibilities of machine learning (ML) in disease detection. This research propose novel technique in detection of Leukemia from smear blood images based on deep learning techniques. Here the input image has been processed for noise removal and image resize with smoothening the image