A Crop Simulation Model (CSM) is a model that helps estimate crop yield as a function of weather conditions, soil conditions, and choice of crop management practices.^{[1][2][3][4][5]}

Crop simulation models have been classified into three broad categories:^[6][7]

1. Statistical models: These typically rely on yield information for large areas (such as counties), and identify broad trends. The two main trends identified are a secular trend of a gradual increase in crop yield, and variation based on weather conditions. Statistical models are a significant improvement over naive historical predictions, but are not preferred for very fine-grained predictions.
2. Mechanistic models: These attempt to use fundamental mechanisms of plant and soil processes to simulate specific outcomes. These involve fairly detailed and computation-intensive simulations.
3. Functional models: These use simplified closed functional forms to simulate complex processes. They are computationally easier than mechanistic models, and can often give results that are of only somewhat worse accuracy. The Penman equation is an example of an equation that might be used as a component of a functional model.

• CropSyst, a multi-year multi-crop daily time-step crop simulation model developed by a team at Washington State University's Department of Biological Systems Engineering.^[3]

• The Climate Corporation