Purpose: The development of optics-based wearables for bladder volume monitoring has emerged as a significant topic in recent years. Given the innovative nature of this technology, there is currently no bladder phantom available to effectively validate these devices against more established gold standards, such as ultrasound. In this study, we showcase and demonstrate the performance of our hybrid bladder phantom by using an optical device and making comparisons with ultrasound. Methods: A series of validation tests, including phantom repeatability, ultrasound scanning, and an optical test, were performed. A near-infrared optical device was utilized to conduct diffuse optical spectroscopy (DOS). Machine learning models were employed to construct predictive models of volume using optical signals. Results: The size and position of an embedded balloon, serving as an analog for the bladder, were shown to be consistent when infused with 100 mL to 350 mL of water during repeatability testing. For DOS data, we present 7 types of machine learningbased models based on different optical signals. The 2 best-performing models demonstrated an average absolute volume error ranging from 12.7 mL to 19.0 mL. Conclusions In this study, we introduced a hybrid bladder phantom designed for the validation of near-infrared spectroscopy-based bladder monitoring devices in comparison with ultrasound techniques. By offering a reproducible and robust validation tool, we aim to support the advancement of next-generation optical wearables for bladder volume monitoring.