Smallholder farming systems in Ghana are crucial for food security and rural development. However, their economic viability is often questioned due to high operating costs. A difference-in-differences approach was employed to analyse changes in farm costs before and after implementing specific interventions. Data were collected from two groups of smallholder farmers: those who received training and inputs (intervention group) and a control group that did not receive these supports. The model accounts for potential confounders through regression analysis. The DID model revealed significant cost reductions in the intervention group, with an estimated reduction of 20% in total farm costs compared to the control group. This finding suggests that targeted interventions can substantially improve economic efficiency among smallholder farmers. This study provides empirical evidence supporting the use of DID models for assessing the cost-effectiveness of agricultural support programmes in Ghanaian smallholder farming systems. The findings suggest that policymakers should prioritise funding and resource allocation to smallholder farmers, particularly those who have demonstrated responsiveness to training and inputs. Future research could explore longer-term effects and scalability of these interventions. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.