Objective: To evaluate the prevalence, patterns, and sociodemographic predictors of wearable device use among individuals with self-reported diabetes mellitus. Methods: Data for our analysis was drawn from cycle 3 (2019) of the 5th edition of the Health Information National Trends Survey (HINTS 5). Descriptive statistics were used to evaluate the demographic characteristics, prevalence, and frequency of wearable device use among individuals with diabetes mellitus. Multivariable logistic regression was used to identify the sociodemographic predictors of wearable device use. Results: We identified 1149 individuals who self-reported diabetes mellitus. Of these, 51.2% were females, 59.3% were white, and 51.6% had less than a college education. The prevalence of wearable device use was 20%. Further, a sizable proportion (86.1%) of the wearable device users were willing to share information from their wearable devices with their healthcare provider, and almost half of them (43.4%) reported daily use of these devices in the past 1-month. Significant sociodemographic predictors of wearable device use include age, income, and level of education. Conclusion: Our results highlight the feasibility and acceptability of using wearable devices to deliver evidence-based health care to individuals with diabetes. Future interventions should consider the scalability of these tools and how to reach those subgroups of individuals with diabetes mellitus to whom current technologies may be unavailable.