Durum wheat (Triticum durum L.) plays a key role for Italian agriculture and for world pasta production. Wheat production largely depends on weather. The aim of this study is to develop an operational tool to supply early forecasts of the final yield. Early forecasts will provide information for a more effective crop management that will help minimizing the uncertainty related to crop production. The climate impact on the yield, and the ability of the Leaf Area Index (LAI) to describe the environmental influences on the crop, were assessed through the model CERES-wheat in a long-term analysis. The results showed a highly significant correlation between yield and the rainfall during the leaf growth and plant tillering stages. A highly significant correlation was also found between yield and the LAI reached at the end of the vegetative season. Then, the number of March non-rainy days and the April LAI were used as independent variables in a multi-regressive model for the final yield estimation. The model was validated with ground measurements to test its ability as a simplified forecasting index. The resulting yield estimates showed highly significant correlation with those observed. The results showed that the forecasting index is suitable for operational farming applications, being able to provide, with a few input data, the first forecasts in early April well in advance to maturity.