Leukemia cancer poses a risk to life as acute or chronic leukemia can manifest themselves more severe symptoms. The most frequent type of leukemia cancer is acute lymphoblastic leukemia (ALL). ALL affects about 20% of adult leukemias and presents in 80% of childhood leukemias. ALL diagnosing is very complex that requires labor-intensive, sophisticated procedures. One of the most important criteria of a healthcare system is to give the patient the best possible care based on an examination of their medical history, lifestyle choices, and any molecular trait variability. Several intelligent technologies that are based on machine learning and data-driven methods have been developed to address these problems. this paper examines statistical and machine learning methods. We also provide a trustworthy cloud-based data storage paradigm and a safe Android-based architecture for gathering patient data. The paper introduces the Leu-Life, a m-health android application that uses machine learning methods to detect leukemia cancer along with providing a set of features that helps in managing and facilitating life of leukemia cancer patients. The discussion will conclude with a predictive algorithm that may categorize leukemia cancer based an input of a blood file.