The increased availability of crime data, coupled with the crime mapping capabilities, has contributed to knowledge concerning the spatial distribution of crime over large areas. However, the type of mapping used in most of these macro-level analyses, choropleth mapping, may mask nuances within the distribution of crime by only offering a map with different shades or textures indicating crime levels and values. On the contrary, dasymetric mapping refines the mapping of crime within a geographic location by using additional data, such as land use and census data, to estimate how crime may be distributed within the units of analysis. This mapping technique can reveal clusters of crimes within a density map; clusters that choropleth maps would mask. The current analysis utilized dasymetric mapping to estimate the distribution of aggregate level burglary within political boundaries in Massachusetts, focusing on land use and housing data. Data were drawn from U.S. Census information and Massachusetts State Police information on residential burglaries. The dasymetric maps produced a description of areas where burglaries were likely to be clustered based on the distribution of potential targets for residential burglary in the specified boundaries. The dasymetric mapping estimation can be refined further by adding variables from census data based on the unit of analysis. As such, the use of dasymetric mapping is suited to researchers working with aggregated data, such as Uniform Crime Reports (UCR) data. Figures, references