This chapter sets strict standard for financial fraud to only include major accounting fraud including false records, misleading statements and material omissions which is identified based on violation typologies and penalty magnitude into the analytical framework. Leveraging the theory of GONE (Greed, Opportunity, Need, Exposure), this chapter implements an innovative two-stage feature selection methodology integrating Pearson correlation coefficients and average feature importance scores, simultaneously validating theoretical foundations of the GONE theory and optimizing machine learning model performance.