The primary goal of this project is to develop a predictive model for clinically significant depressive symptoms (CSDS) in patients undergoing coronary artery bypass graft (CABG) surgery, using pre- and perioperative data. CSDS occur in about 30 percent of CABG patients, which is four times higher than in the general population. These symptoms are linked to poor quality of life and increased morbidity and mortality. The aim is to create a model that can identify patients at risk for postoperative depression. This tool could help clinicians make informed decisions and take preventive measures to manage depression after surgery.