Objective: This research utilizes the FAERS for data mining to identify heart-related side effects caused by opioids, ensuring the safe use of these medications. Methods: Data from 79 quarters (Q1 2004 to Q3 2023) involving adverse event (AE) reports for opioids like morphine and oxycodone was reviewed. We applied the MedDRA system to categorize events and used statistical tools, ROR and BCPNN, for signal detection. These findings were cross-checked with drug labels and SIDER 4.1 for accuracy. Identified risks were then categorized by severity using DME and IME classifications. Results: Analysis of adverse events (AEs) for the five examined drugs (35359, 14367, 144441, 10592, and 28848) identified 33, 6, 12, 37, and 34 cardiovascular AEs, and 16, 5, 7, 25, and 21 instances of important medical events (IMEs) respectively. Each drug was linked to cases of cardiac and cardiopulmonary arrest. The cardiovascular AEs varied widely in occurrence and severity, with methadone notably presenting diverse and potent risks, including sudden cardiac death as a distinct medical event (DME). A comparison with SIDER 4.1 showed 11 opioid-related cardiovascular AEs in line with our findings. Standardized MedDRA Queries (SMQs) confirmed these results, indicating stronger signals for methadone and tramadol, while morphine, hydromorphone, and oxycodone exhibited fewer and weaker signals. Conclusion: The study revealed numerous heart-related adverse effects (AEs) not listed on drug labels and identified new AE patterns. Recognizing these differences in AE profiles and risks across different opioids is crucial for safer prescription practices to minimize cardiac complications.