Rwanda has implemented various agricultural interventions to improve smallholder farm productivity, but the effectiveness of these programmes is often uncertain. A comprehensive literature search was conducted to identify studies applying DiD methods. Studies were evaluated based on the quality of data and analytical techniques used, including robustness checks. One study found that a 45% increase in fertilizer use was associated with agricultural training programmes (95% CI: 20-70%). DiD models are effective for measuring adoption rates but require careful consideration of model assumptions and potential confounders. Future research should validate findings using additional data sources and control for unobserved heterogeneity. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.