Agricultural credit forms an important plank of financial inclusion policies in developing countries, yet evaluations of its impact on borrowers’ wealth status are very few owing to significant problems of identification. Using national data from India that constitutes a short panel, I use matching techniques to evaluate this impact for a sample of farmer households, by matching on covariates that were measured before a proportion of these households availed of loans. I then select the most suitable matching technique based on the extent of covariate balance that results from matching, as evaluated by standardized bias plots, quantile-quantile plots, and summary measures of the latter. I find evidence of a positive treatment effect and discuss the robustness of the findings through checks for sensitivity and consistency.