Background and Objectives: Perioperative myocardial infarction (PMI) after coronary artery bypass grafting (CABG) remains difficult to diagnose due to varying biomarker thresholds and ECG criteria. This study aimed to evaluate the predictive value of ECG changes and cardiac biomarkers for identifying pathological findings in repeat coronary angiography after CABG. Materials and Methods: This retrospective study included 137 patients who underwent repeat coronary angiography due to suspected PMI. ECG changes and serial measurements of CK, CK-MB, and hsTnT were analyzed at 4, 8, and 18 h postoperatively. The primary endpoint was the identification of graft-related complications or new coronary lesions. Results: Pathological angiographic findings were detected in 85.4% (n = 117) of cases, predominantly graft-related complications (96.6%). ST-segment elevation (p < 0.01) and ST-segment depression (p = 0.02) were significantly associated with pathological findings. The combination of ST-segment elevation and CK-MB > 1.0 µkat/L also showed a high predictive accuracy (p < 0.01). HsTnT demonstrated the strongest diagnostic performance, with a threshold of 1231 ng/L at 18 h (AUC = 1.0; p < 0.01). Earlier postoperative biomarker elevations did not show significant discriminatory value. Conclusions: ECG remains the most accessible and fastest predictive tool for PMI detection. However, cardiac biomarkers only gain diagnostic relevance beyond 8 h postoperatively. A multimodal approach integrating biomarker kinetics and ECG changes may enhance early decision-making and improve patient outcomes, as ST-segment elevation in combination with CK-MB > 1.0 µkat/L serves as a relevant predictor. Notably, hsTnT levels > 1231 ng/L at 18 h reliably identified patients with pathological angiographic findings. These findings were derived from a highly selected cohort (~2% of all CABG patients) referred for coronary angiography and should therefore be interpreted as hypothesis-generating rather than directly generalizable to the broader surgical population.