Maize yield productivity in Ethiopia has been below the genetic potential—constrained, among other factors, by frequent moisture stress due to local weather variability. Changes in climate may exacerbate these limitations to productivity, but current research on projecting responses of maize yields to climate change in Ethiopia is inadequate. The research objectives of this project were to (1) calibrate and evaluate the performance of the APSIM-maize and DSSAT CSM-CERES-Maize models, and (2) assess the impact of climate change on future maize yield. The climate periods considered were near future (2010–2039), middle (2040–2069) and end of the 21st century (2070–2099). Climate simulations were conducted using 20 General Circulation Models (GCMs) and two Representative Concentration Pathways (RCPs; RCP4.5 and RCP8.5). Both crop models reasonably reproduced observations for time to anthesis, time to physiological maturity and crop yields, with values for the index of agreement of 0.86, 0.80 and 0.77 for DSSAT, and 0.50, 0.89 and 0.60 for APSIM. Similarly root mean square errors were moderate for days to anthesis (1.3 and 3.7 days, for DSSAT and APSIM, respectively), maturity (4.5 and 3.1 days), and yield (1.1 and 1.2 tons). Deviations of simulated from observed values were low for days to anthesis (DSSAT:-2.4–2.3%; APSIM: 0–6%) and days to maturity (DSSAT: -0.6–4.4%; APSIM: -1.9–3.3%) but relatively high for yield (DSSAT: -18.5–21.2%;APSIM: -19.1–37.1%). Overallthe goodness-of-fit measures indicated that models were useful for assessing maize yield at the study site. Simulations for future climate scenarios projected slight increases in the median yield for the near future (1.7%–2.9% across models and RCPs), with uncertainty increasing toward mid-century (0.6–4.2%). By the end of the 21st century, projections ranged between yield decreases by 6.3% and increases by 4%. Differences betweentheRCPs were small,probablydue to factor interactions, suchashigher temperatures reducing the CO2-induced yield gains for the higher RCP. Uncertainties in studies on the impact of climate change on maize might arise mostly from the choice of crop model and GCM. Therefore,the use of multiple crop models along with multiple GCMs would be advisable in order to adequately consider uncertainties about future climate and crop responses and to provide comprehensive information to policy makers and planners. Overall, results of this study (based on two different crop simulation models across 20 GCMs, and two RCPs under similar crop management) consistently indicated a slight increase in yield.