Planning of crops for the next season has been a tedious task for the farmers as it is a difficult prediction about metrics of prices that their crop will fetch in a particular season which will be typically based on dynamic weather conditions. This leads to inaccurate prediction of crops’’ prices by farmers, and they happen to wrongly select the crops or in haste they happen to sell their crops early without storing and thus earning less than what the same crop would have fetched them in the future. This problem could be addressed by an ML model which will predict the prices of crops in advance showing the proper analysis of the crop and presenting their future scenario so that farmers can select the right crops to strategize crop production which involves crop selection, time of sowing deciding crop pattern and storage of harvested crops providing enough insights for predicting the appropriate price in the markets.

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