Estimating winter wheat yield through the decreasing phase of its green area. A large number of agrometeorological models for crop yield assessment are available with various levels of complexity and empiricism. However, the current development of models for wheat yield forecasting does not always reflect the inclusion of the loss of valuable green area and its relation to biotic and abiotic processes in production situation. In this study the senescence phase of winter wheat (Triticum aestivum L.) is monitored through the GAI (Green Area Index), calculated from digital hemispherical photographies taken over plots in Belgium, Grand-Duchy of Luxembourg and France. Two curve-fitting functions (modified Gompertz and modified logistic) are used to describe the senescence phase. Metrics derived from these functions and characterizing this phase (i.e. the maximum value of GAI, the senescence rate and the time taken to reach either 37% or 50% of the green surface in the senescent phase) are related to final grain yields. The regression-based models calculated with these metrics showed that final yield could be estimated with a coefficient of determination of 0.83 and a RMSE of 0.48 t·ha-1. Such simple models may be considered as a first yield estimates that may be performed in order to provide a better integrated yield assessment in operational systems. Indeed, estimation of cereal-crop production, particularly wheat, is considered as a priority in most crop research programs due to the relevance of food grain to world agricultural production.