IgA nephropathy (IgAN) is the leading cause of end-stage renal disease in Asia, affecting over 1.5 individuals per 100,000 worldwide annually. In 2019, the International IgAN Prediction Tool(IIgAN-PT) was proposed (Fig 1), which utilizes clinical variables and the pathologic results of renal biopsy(MEST score) as predictors. However, its dependence on invasive biopsy limits its utility and makes repeated evaluation during the treatment period difficult. The purpose of this study is to develop a model that can predict the prognosis of IgAN patients by estimating the MEST score based on radiomics information extracted from precontrast CT of histologically proven IgAN patients.