Asian Indians are becoming a larger share of the total U.S. population and represent nearly 20% of the Asian American subgroup. However, they are often understudied in disability research. To overcome this gap, the present paper utilized the 2012–2016 American Community Survey to conduct an exploratory and spatial analysis of disability for older Asian Indians (i.e., 60 + years of age). Results from the logit analyses revealed an increased likelihood for any disability at older ages with an odds ratio of 1.08. Meanwhile, male [OR 0.63–0.81, 95% CI], currently married [OR 0.66–0.88, 95% CI], Medicare recipients [OR 0.39–0.56, 95% CI], individuals with private insurance [OR 0.42–0.58, 95% CI], and those with higher levels of education exhibited a reduced probability for having any disability. Subsequent regression analyses with state-level variables (i.e., California, Illinois, New Jersey, and New York) resulted in similar estimates. The analyses with metropolitan-level variables revealed the Illinois region (Chicago-Naperville area) exhibited a greater likelihood while the northern region of California (San Jose-Sunnyvale-Santa Clara and Oakland-Hayward areas) exhibited a lower likelihood for any disability. An additional semi-nonparametric model, which relaxed the assumption of a logistic distribution of the error terms, produced similar results. Further exploratory spatial analyses were conducted for the two statistically significant areas: Illinois and northern California. Results showed a high concentration of disability in the Bloomingdale, Schaumburg, Wayne, and Winfield Townships (Chicago-Naperville metropolitan division) and in Fremont and Union Cities (San Jose-Sunnyvale-Santa Clara and Oakland-Hayward areas). Results from this study can better inform community health workers about the socio-economic factors related to disability and which areas to target for health and wellness interventions to improve functional mobility.