Computational modeling demonstrates that wearable photoplethysmography (PPG) sensors can track abdominal aortic aneurysm diameter changes with 0.65mm median accuracy by analyzing peripheral pulse waves. The framework aggregated 1,600 measurements and used Bayesian estimation to achieve clinically relevant precision across 50 virtual patients over 12-month simulations. This represents a significant advance in cardiovascular monitoring, as abdominal aortic aneurysms affect over 1% of adults above 50 and carry substantial mortality risk when they rupture. Current surveillance relies on imaging every 6-24 months, creating dangerous gaps where rapid growth acceleration goes undetected. Continuous monitoring through consumer-grade wearables could transform aneurysm management by enabling real-time detection of growth patterns that warrant immediate intervention. However, this computational proof-of-concept faces substantial translation challenges. The modeling relied on simplified hemodynamics and virtual patients rather than real-world validation. Actual PPG signals contain motion artifacts, ambient light interference, and individual anatomical variations that could degrade performance. As a preprint awaiting peer review, these promising results require validation in clinical trials with actual patients and commercial PPG devices before determining practical utility. The approach remains intriguing for its potential to democratize sophisticated cardiovascular monitoring.