We built an easy-to-interpret individual vulnerability index to floods that is amenable for empirical testing and may be adapted to any perceived hazard or ecological setting. An individual’s vulnerability value (Vi) was estimated from characteristics unique to him/her, added to those he or she shared with people sleeping in the same building, then by all members of his or her household and finally by all community members. Vi was obtained for 994 individuals living in 129 domestic units in 14 rural populations from three subregions in the Grijalva River Basin, Tabasco, Mexico. The Vi means of Wetland subregion communities were significantly lower than those of Mountain and Coastal Plain regions. Bivariate correlations allowed us to identify those variables that had a greater influence on the estimation of Vi in general, and which correlated most with Vi per region. Knowing which variables increased vulnerability allowed us to make policy suggestions to target each region’s specific needs. We argue that this bottom-up approach gives the index a value that reflects individual conditions and interactions that affect vulnerability that other indices derived from larger aggregation-level data are incapable of providing.