In this era, with the technology used in every field, the agriculture market also generates a huge amount of revenue every day. Computer technology plays a vital role in managing and finding meaningful information about it. To manage large datasets, a field that integrates data mining, machine learning, mathematics, computer applications, and artificial intelligence is used. Crop price forecasting is a demanding and interesting method for the agricultural sector because it is dependent on future crop production worldwide. The maximum crop price for the current session or the next year is something that the entire agriculture community is interested in knowing. Currently, crop price analysis dominates the study instead of agriculture crop amount forecast. In comparison to other nations, crop yield in India is quite uneven when measured by the agriculture fraternity. It is insufficient as a base rate for any chosen crop price if an appropriate MSP is not provided. There may be a decrease in Indian poverty when these farmers receive or determine fair crop prices. A vast amount of commodity data is produced in agriculture today. A significant amount of commodity data is produced by the agriculture sector, but sadly, most of this data is not utilized to uncover hidden information. Machine learning algorithms are used to make a machine think like a human, comprehend the data sets that are currently available, and compare them to similar events that have happened in the past.