his paper provides an analysis on the technical efficiency of iron biofortified bean production in Rwanda, as well as recommendations for implementation of targeted biofortification programs. We employ a three-pronged approach to examine efficiency across matched pairs of treated (i.e., grew iron biofortified beans) and control (i.e., grew other improved or traditional beans) bean growing households. First, bean growing households (treatment and control) were matched by using the spatial propensity score matching (PSM) approach. Second, efficiency was estimated using spatial autoregressive models and non-spatial stochastic frontier models on the three data groups: treatment, control, and pool. Third, an econometric analysis was conducted to explore factors affecting farmers’ efficiencies. All these steps were implemented separately for farmers who grew bush beans and for those who grew climbing beans. Results showed that for both types of bean growers, farmers who grew iron biofortified varieties were relatively more efficient and obtained greater bean production (by 3 percent for bush and 13 percent for climbing) than the control group. A spatial univariate clustering spatial analysis on farmers efficiency helped identify geographic areas in which farmers with high technical efficiency (i.e., hotspots) and low technical efficiency (i.e., cold spots) were located, and can be reached through targeted, tailor-made interventions.