Non-alcoholic fatty liver disease (NAFLD) is a systemic disorder with a complex multifactorial pathogenesis and heterogenous clinical manifestations. NAFLD is the most common cause of chronic liver disease in many countries worldwide. It is already highly prevalent in the general population, and owing to a rising incidence of obesity and diabetes mellitus, the incidence of NAFLD and its impact on global healthcare are expected to increase in the future. A subset of patients with NAFLD develops progressive liver disease leading to cirrhosis, hepatocellular carcinoma, and liver failure. NAFLD has emerged as one of the leading causes of cirrhosis and hepatocellular carcinoma in recent years. Compared with the general population, NAFLD increases the risk of liver-related, cardiovascular and all-cause mortality. NAFLD increases the risk and contributes to aggravation of the pathophysiology of atherosclerosis, cardiovascular diseases, diabetes mellitus, and chronic kidney disease. The increasing global prevalence of NAFLD is mainly attributed to the silent manifestation of the disease, which is often disregarded by the common population. To address the increasing burden of NAFLD, it is necessary to identify early signs of the disease and implement diet and lifestyle modifications and natural treatment modalities to delay or alleviate disease onset. The aim of our study is to validate an algorithm designed for early prediction of NAFLD among healthy Indians. The algorithm also indicates the severity of the disease and indicates a suitable disease management plan accordingly. In addition to that we aim to predict and analyze the parameters which lead to severity of NAFLD, its faster progression to cirrhosis and poorer prognosis. This will help to create a predictive analysis model which can be used to educate and guide the patients by means of graphic visualization of their health condition if corrective steps are not taken. As we know, human beings present with different attitudes and mental dispositions. Some of them promptly switch over to a healthier lifestyle on receiving the diagnosis of NAFLD or any lifestyle disease. But unfortunately, most patients we encounter, show laid back approach towards their health, partly due to lack of motivation and partly because of the paucity of knowledge where their present state of health can land them if they do not take adequate corrective steps. There is nothing better than a visual depiction of their prognosis (if the disease parameters progress at the present rate) to impress upon them the necessity of care to prevent the dreaded prognosis. The data collected by this platform will help to create a base for the predictive analysis model with and without corrective measures and a visual depiction of future prognosis.