A crop yield prediction system using a machine learning-based prediction model according to an embodiment of the present invention includes information on a plurality of crops and the amount of sunlight irradiated during a predetermined period for each of the plurality of crops. A data storage unit in which an average value and yield data of each of the plurality of crops are stored, and an average value of the amount of sunlight irradiated during the predetermined period for each of the plurality of crops is set as an input, and the plurality of crops By performing the machine learning by putting the yield data of each of them as an output, a prediction model generator and a manager generating a prediction model for calculating the predicted yield data as an output when an average value of solar irradiation is applied as an input, by a manager When the information on the first crop among the plurality of crops and the average value of the first solar irradiation amount are applied as inputs, when a command for predicting yield data for the first crop is applied, the first sunlight is applied to the prediction model. It includes a calculation unit for applying the average value of the irradiation amount as an input to calculate the first yield data corresponding to the average value of the first solar irradiation amount and a data display unit for displaying the first yield data on the screen.
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