Crop rotations have become increasingly popular recently due to their importance to the farming industry. The greatest issue with crop rotations is that the long-term weather predictions required to compose crop rotations are not yet meeting the levels of accuracy wanted to ensure that the correct crops are planted each rotation. To solve this problem, we are aiming to create an easily understandable interface that requires an input of the users coordinates and returns an output of the crops most likely to succeed within the next crop rotation period associated with the coordinates of the user. We are looking to combine temperature data, sunlight exposure data, and precipitable water estimates to create weather predictions for the ten Canadian provinces over the next three years. These predictions will then be linked to the coordinates of the stations where the data was taken from. Once the weather predictions are completed, they will then be compared to our database of the ideal weather conditions for each type of crop, to return which crops will do the best under the weather conditions predicted at this location. These ideal crop predictions would then be stored within the website so that coordinates can be input to receive the return of what crops are predicted to have higher success rates and what the weather predictions are within the specified area.