Background: Abdominal aortic aneurysm (AAA) patients are at increased risk of major adverse cardiovascular events (MACE). Currently, no AAA-specific clinical tools are available to accurately predict this risk, necessitating an individualised risk stratification model. Objective: This study aimed to develop and validate a simple clinical risk score (Q-ACE score) to predict the risk of MACE in patients with abdominal aortic aneurysm. Methods: A retrospective analysis was conducted on 371 patients with small asymptomatic AAA from three Queensland hospitals between 2002 and 2019. A Cox proportional hazards model was built using stepwise selection, identifying key variables predictive of MACE. The dataset was randomly divided into a training cohort (60%) and a validation cohort (40%) to develop and validate the Q-ACE score. A parsimonious cox proportional hazards model was developed with clinical variables included based on stepwise selection and refined using importance via Breiman permutation. The point score was developed based on rounded beta-coefficients and assessed using the validation cohort. Model performance was assessed through concordance statistics (c-statistics) and Kaplan-Meier analyses. Results: The final risk model included age ≥75 years, gender, diabetes, AAA diameter ≥50mm, and chronic kidney disease (CKD) stage ≥3B. The Q-ACE score exhibited good discrimination in the training (c = 0.70; 95% CI: 0.58-0.80) and validation cohorts (c = 0.73; 95% CI: 0.64-0.82). Patients classified as high risk had a significantly increased hazard of MACE (HR = 2.5; 95% CI: 1.25-5.01) compared with low-risk patients (HR = 0.28; 95% CI: 0.12-0.64). Conclusion: The Q-ACE score provides a clinically relevant tool for predicting cardiovascular risk in AAA patients, demonstrating good discrimination and potential for guiding individualised secondary prevention strategies. Further validation in larger, diverse cohorts is necessary to confirm these findings.