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Background: Incident fatty liver increases the risk of non-alcoholic fatty liver disease (NAFLD), which may lead to end-stage liver diseases, and increase the risk of cardiovascular disease and diabetes. For its prevention, modeling the natural history of fatty liver is useful to demonstrate which lifestyle-related risk factors (e.g. body mass index and cholesterol) play the greatest role in the life-course of fatty liver., Methods: Model predictors and their predictive algorithms were determined by prospective regression analyses using 5-year data from approximately 2000 Japanese men aged 20-69 years. The participants underwent health examinations and completed questionnaires on their lifestyle behaviors annually from 2012 to 2016. The life-course of fatty liver was simulated based on this participant data using Monte Carlo simulation methods. Sensitivity analyses were performed. The validity of the model was discussed., Results: The body mass index (BMI) and low-density/high-density lipoprotein cholesterol (LDL-C/HDL-C) ratio significantly aided in predicting incident fatty liver. When the natural history of fatty liver was simulated using the data of participants aged 30-39 years, the prevalence increased from 20% to 32% at 40-59 years before decreasing to 24% at 70-79 years. When annual updates of BMI and LDL-C/HDL-C ratio decreased/increased by 1%, the peak prevalence of fatty liver (32%) changed by -8.0/10.7% and -1.6/1.4%, respectively., Conclusions: We modeled the natural history of fatty liver for adult Japanese men. The model includes BMI and LDL‒C/HDL‒C ratio, which played a significant role in predicting the presence of fatty liver. Specifically, annual changes in BMI of individuals more strongly affected the life‒course of fatty liver than those in the LDL-C/HDL-C ratio. Sustainable BMI control for individuals may be the most effective option for preventing fatty liver in a population., Competing Interests: MA, SI, MM and MK have no competing interests. KA is an employee of Fujikura Ltd., but had no control over the data collection or analysis of this work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.