A continuous increase in global population growth combined with existing limited resources in agriculture raise concern of what is needed to meet future food demand. Furthermore, an increase in climate seasonal variability due to climate change will also affect the overall productivity in agriculture. This study aims to test the usefulness of seasonal forecast in increasing wheat production. By introducing ahead of time knowledge of upcoming seasonal forecast, it will be analyzed if increases in food production can be achieved using fewer resources through adopting season-specific management practices for each year. The objective is to determine how seasonal climate forecasting, considered as a risk management tool, improves management practices in wheat cropping. Using a crop simulation model, it will be tested if seasonal climate forecasting can be used to differentiate between potentially high-yielding seasons (“good seasons”) and potentially low-yielding seasons (“poor seasons”). Then, using this information, season-specific management practices will be determined to maximize returns from optimized yields. Finally, it will be tested if by using the seasonal climate forecasting over a period of time, an overall higher average yields can be obtained at a lower average operational cost.