For this study, we evaluated three machine learning models—Random Forest (RF), SVM, and XGBoost—for their ability to accurately classify amyloidosis samples into the four most common subtypes (AA, ALκ, ALλ, and ATTR), as well as ACal, ApoAI, and ApoAIV amyloidoses. This evidence concerns the gene BCR and amyloidosis.