Information on the spatial distribution of poverty can be useful in designing geographically targeted rural poverty reduction programs. This paper uses recently released município-level data on rural poverty in Brazil to identify and analyze spatial patterns of rural poverty in the São Francisco River Basin (SFRB). Moran's I statistics are generated and used to test for spatial autocorrelation, and to prepare cluster maps that locate rural poverty 'hot spots' and 'cold spots.' Research results demonstrate that rural poverty is spatially correlated in some parts of the SFRB, and where correlated, worse-off (better-off) municípios tend to be located next to worse-off (better-off) municípios. The policy implications of these results are discussed, as are proposed next steps in research.