Abstract The built environment possessed determinants of more active lifestyles, related to social and cultural reality. Thus, relevant walkability variables in large cities and in developed countries may not be suitable for mid-sized Brazilian towns. Therefore, from a case study, the objective of this research was to evaluate the relevance of eight objective walkability variables: Residential Density; Retail Floor Area Ratio; Mixed Land Use (Entropy); Space Syntax - Integration and Choice; Land and Real Estate values in a case study of a mid-sized Brazilian town. From the geocoding of data from the Municipal Urban Mobility Plan, urban form variables were aggregated and tested in 1000 meter network buffers. Analyzes were performed using a machine learning approach, through the Random Forest algorithm, in relation to self-reported walking (meters walked per unit of area). Results indicated that the most relevant characteristics were: Entropy, Integration within a 2000 meter radius and Residential Density. Contributions include the possibility of subsidizing urban planning policies in adopting an evidence-based approach.