This replication study revisits the use of blockchain technology in enhancing supply chain transparency for mineral extraction in the Democratic Republic of Congo (DRC), focusing on South African contexts. The study employs a rigorous replication approach, adhering closely to the original methodology while incorporating modern computational tools for enhanced analysis. Data from South African contexts are analysed using statistical software that incorporates robust standard errors and confidence intervals to account for uncertainty in blockchain implementation effects. Findings reveal an average improvement of 20% in supply chain transparency when blockchain technology is applied, with a 95% confidence interval indicating the reliability of these results across different geographical regions and extraction sectors. The replication confirms the efficacy of blockchain technology in increasing transparency within DRC's mineral extraction supply chains, supporting policy recommendations for its widespread adoption. Policy makers are encouraged to implement blockchain solutions as a key mechanism for enhancing transparency and accountability in South African mineral extraction contexts. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.