Satellite-based techniques that provide temporally and spatially continuous information over vegetated surfaces have become increasingly important in monitoring the global agriculture yield. However, it remains challenging to model crop yields based on remotely sensed data. In this study, we examine the performance of a light use efficiency model (EC-LUE) for simulating the Gross Primary Production (GPP) and yield of crops. The EC-LUE model can explain on average approximately 90% of the variability in GPP for 36 FLUXNET sites globally. The results indicate that a universal set of parameters, independent of crop species (except for C4 crops), can be adopted in the EC-LUE model for simulating crops' GPP. At both irrigated and rainfed sites, the EC-LUE model exhibits a similar level of performance. However, large errors are determined when simulating yield based on crop harvest index. This analysis highlights the need to improve the representation of the harvest index and carbon allocation for improving crop yield estimations from satellite-based methods.