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Development programs have typically neglected uncertainty and variability in terms of outcomes and socio-ecological context when promoting conservation agriculture (CA) throughout sub-Saharan Africa. We developed a simple Monte Carlo-based decision model, calibrated to global data-sets and parameterized to local conditions, to predict the range of yield benefits farmers may obtain when adopting CA in two ongoing agricultural development projects in East Africa. Our general model predicts the yield effects of adopting CA-related practices average −0.60 ± 2.05 (sd) Mg maize ha⁻¹ year⁻¹, indicating a near equal chance of positive and negative impacts on yield. When using site-specific, socio-economic, and biophysical data, mean changes in yield were more negative (−1.29 and −1.34 Mg ha⁻¹ year⁻¹). Moreover, practically the entire distributions of potential yield impacts were negative suggesting CA is …