Patients with ischemic heart disease are associated with poor prognosis, and their number has increased globally. Therefore, biomarkers that could predict post-acute myocardial infarction (AMI) heart failure (HF) would be helpful to guide appropriate treatment. Based on the diagnosis on admission and results of echocardiogram performed on admission and 1 year after discharge, the current study recruited 54 patients with post-AMI HF, 59 patients with post-AMI non-HF, and 59 healthy controls. Eight candidate microRNAs (miRs) were screened through real-time quantitative PCR. Serum circulating miR-150 level in the post-AMI HF group was significantly lower than the post-AMI non-HF group (0.4 ± 0.3 versus 0.7 ± 0.3, P < 0.001). Further analysis showed that serum circulating miR-150 level was associated with ejection fraction (EF) 1 year after discharge (P < 0.001). Receiver operating characteristic curve (ROC) analysis found that area under the ROC (AUC) was 0.616 (95%CI = 0.511-0.721, P = 0.034) when BNP was used to predict post-AMI HF, whereas AUC improved to 0.764 (95%CI = 0.674-0.855, P < 0.001) when miR-150 was used. The combination of BNP and miR-150 significantly improved the AUC to 0.807 (95%CI = 0.727-0.886, P < 0.001). Finally, multivariate logistic regression analysis revealed that either LVEF on admission or serum circulating miR-150 level was independently associated with post-AMI HF. Serum circulating miR-150 is a novel biomarker to predict post-AMI HF. Further large sample prospective clinical research is needed to validate its role in the future.