With the rapid increase in the implementation of new technology and the development in precision farming applications, the necessity of near real-time tools to estimate final yield has also increased. During the last 20 years many mathematical models and Decision Support Systems have been developed. These systems use information about weather, soil, and a farmer's management practice to estimate crop growth and yield. Their most advanced feature is the capability to predict future yield. However, these models need to be supplied with weather forecast information to insure the proper estimations of growth and development for the current growing season. In this study the possibilities to estimate weather effect on plant growth, using weather forecast data were determined. Weather Services International, Inc. supplied weather forecasts on a daily basis for more than 30 locations in central and southern USA. A simplified version of the Soybean Decision Support System - PC-Yield, based on the soybean simulation model CROPGRO, was used. For the 1997 growing season the accuracy of the weather forecasts and the quality of the weather data, as well as their impact on yield predictions were determined. Results for South Georgia showed that for rainfed conditions projected yield decreased over time, while for irrigated conditions projected yield increased over time. Dry periods during the summer months created ample water stress, which affected crop growth and final yield. The weather forecasts as well as soybean yield predictions will be further evaluated for the 1998-growing season.