The evaluation of cost-effectiveness in smallholder farm systems is critical for enhancing agricultural productivity and sustainability in resource-limited environments such as Kenya. A key component involves the application of a linear regression model to analyse data from the randomized trial, accounting for potential confounding variables such as climate and soil type. The model is represented by \(Y = \beta_0 + \beta_1X_1 + \epsilon\), where Y represents yield outcomes, X1 denotes input costs, and \(\epsilon\) accounts for measurement errors with a standard deviation of 5%. This study provides essential insights for policymakers and agricultural practitioners aiming to improve the efficiency and sustainability of smallholder farming systems in Kenya. The findings underscore the importance of integrating organic inputs into farm management strategies. Future research should validate these results across different climatic regions and soil types to ensure broad applicability.