This paper investigates the spatial distribution of heavy metals (HMs) concentrations in road dusts over a part of the Brussels-Capital Region (BCR), with the aim of identifying the most relevant factors impacting these concentrations and subsequently mapping them over all road segments. For this goal, a set of 128 samples of road dusts was collected over a three years time span in the Anderlecht municipality, that covers about a tenth of the BCR area. The concentrations of Cd, Cr, Cu, Ni, Pb and Zn have been measured in the finest fraction (⌀<250 μm) using ICP-OES. In parallel, continuous and categorical-valued proxies have been collected over all road segments. Using a multivariate linear modeling (MLR) approach, the most influential proxies that have been identified are the distance to the center of the BCR, land use, road hierarchy and roadside parking occupation. The performance of the MLR models remains however limited, with adjusted R2 values around 0.5 for all HMs. From a spatial analysis of the regression residuals, it is likely that some useful proxies could have been overlooked. Although these models have clear limitations for reliably predicting HMs concentrations at specific locations, the corresponding maps drawn over all road segments provide a useful overview and help designing sound monitoring policies as well appropriate implementation of mitigation measures at places where road dust pollutants tend to concentrate. Further studies are needed to confirm this, but it is expected that our models will perform reasonably well over a large part of the BCR. It is believed too that our findings are relevant for modeling road dusts pollution in other cities as well.