Walkability indices are currently used for a wide range of research and commercial applications. Few studies have examined the relationship between walkability indices and measured pedestrian volume or walking rates, nor explored moderators of pedestrian volume such as weather. With 14 years of traffic study data from the City of Ottawa, a spatial auto-regressive (SAR) multi-level model (MLM) was used to understand the proportion of variance in walking explained by the commercial Walk Score® index and selected weather variables. Modeling revealed that a significant proportion of pedestrian volume at a given location in Ottawa, including its spatial lag, was explained by the corresponding Walk Score® value and its spatial lag (51.45%). Furthermore, weather expressed as a combination of ‘felt’ temperature, presence or absence of precipitation, and percent cloud cover, accounted for 2.79% of the variance in walking. These findings indicate that walkability indices may provide value as cost-effective engineering and urban planning tools.