We tested the accuracy of maize simulations using temperature-derived daily solar radiation (DSR) against simulations using measured DSR. The test involved 20 sites in the US North Central Region, including Iowa, South Dakota, Nebraska, Kansas and eastern Colorado. We used two methods to estimate DSR from daily maximum and minimum temperatures. One method is the Mahmood and Hubbard method or M-H method, the other is the FAO method. The M-H method was derived specifically for the US North Central region, while the FAO method is a generic scheme for global continental regions. We obtained long-term weather records of each site with on average 19 years of data from the High Plains Regional Climate Center hosted in the University of Nebraska at Lincoln. All weather data sets have complete daily observations for crop simulation. We used the Hybrid-Maize model to simulate maize yield using both estimated DSR and measured DSR. In general, estimated DSR agreed well with the measured DSR in July and August, while estimated DSR tended to be greater than measured DSR in other months of the growing season. The M-H method performed better than the FAO method in estimating DSR. For grain yield simulation, the overall mean results using DSR by both methods agreed closely with the results using measured DSR (12.3, 12.7 and 12.4 Mg/ha by the M-H method, FAO method and measured DSR, respectively). For stover biomass simulation, the overall mean results using DSR by the M-H method also agreed well with the results using measured data, while the results using DSR by the FAO method was significantly greater than those using measured data. In the US North Central Region, maize yield simulations using DSR derived from daily temperatures by the M-H method are feasible, particularly for studies of long-term yield trend.