New-onset atrial fibrillation (NOAF) is a frequent complication among patients with non-ST-elevation myocardial infarction (NSTEMI) and is associated with adverse outcomes, making early identification of predictors essential for risk stratification and management. This retrospective cohort study evaluated the prognostic value of the Clinical SYNTAX Score (CSS) compared with the anatomical SYNTAX Score (SS), GRACE, and CHA2DS2-VASc scores in predicting in-hospital NOAF and long-term outcomes among 979 NSTEMI patients undergoing coronary angiography. Predictors of NOAF, all-cause mortality, and major adverse cardiovascular events (MACE: death, myocardial infarction, stroke) were identified using logistic and Cox regression models, with receiver operating characteristic (ROC) analysis used to compare the discriminative power of CSS against SS, GRACE, and CHA2DS2-VASc over a median follow-up of 86 months (IQR: 0.1–144). NOAF developed in 80 patients (8.2%), with age, female gender, left atrial diameter, left ventricular diastolic dysfunction, and CSS (p=0.014) identified as independent predictors. CSS demonstrated superior discriminative ability (AUC: 0.724; 95% CI: 0.673–0.775) compared with SS (AUC: 0.644; 95% CI: 0.588–0.699), and a CSS threshold ≥17.77 predicted NOAF with 75% sensitivity and 65% specificity. In Cox regression analysis, in-hospital NOAF, age, hypertension, reduced ejection fraction (<60%), and CSS independently predicted long-term all-cause mortality, while NOAF, EF<60%, age, early AF recurrence, hypertension, and CSS independently predicted MACE; SS was not a significant predictor in either model. These findings indicate that CSS outperforms SS in predicting in-hospital NOAF and long-term outcomes in NSTEMI patients, offering a practical and comprehensive tool for early rhythm monitoring and risk-guided management.