This study is intended to explore the potential of silver (Ag) nanoparticle-based plasma surface-enhanced Raman spectroscopy (SERS) for providing a rapid and simple "Yes/No" assessment to detect acute myocardial infarction (AMI). A simple, rapid, and accurate method of diagnosing AMI is critical to reduce mortality and improve prognosis. Techniques such as electrocardiography examination and use of cardiac troponins have not yet met the current clinical need. Therefore, alternative approaches need to be developed. Plasma samples from 32 patients with AMI and 32 healthy control (Clt) subjects were assessed. Multivariate statistical techniques, including principal component (PC) analysis and linear discriminant analysis (PCA-LDA), were employed to develop a diagnostic algorithm for differentiating between patients with AMI and Clt subjects. Furthermore, the receiver operating characteristic was tested to evaluate the performance of the PCA-LDA algorithm for AMI detection. Each plasma sample was mixed with an equal volume of Ag colloidal solution, and the SERS measurement of each plasma sample was performed. The plasma SERS spectrum showed much stronger and sharper peaks compared with the normal Raman spectrum. Tentative assignments of Raman spectroscopy bands showed specific biomolecular (e.g., proteins, adenosine, adenine, and uric acid) changes. PC analysis and LDA were employed to discriminate patients with AMI from Clt subjects, yielding a sensitivity of 87.5% and a specificity of 93.8%. The findings of this study suggest that plasma SERS has a great potential for improving AMI in the future, and this will certainly reduce the difficulty, time to draw blood, and patients' pain to a great extent.