Agriculture is the basic source of food supply in all the countries of the world—whether underdeveloped, developing or
developed. Not only providing food, this sector has contributions to almost every other sector of a country. According to the
Bureau of Statistics (BS), 2017, about 17 % of the country’s Gross Domestic Product (GDP) is a contribution of the agricultural
sector, and it employs more than 45% of the total labour force. In the decreasing crop production and shortage of food across
the world, one of the crucial criteria of agriculture now-a-days is selecting the right crop for the right piece of land at the right
time. Hence, in our research we have proposed a method which would help suggest the most suitable crops for a specific land
based on the analysis of the data of previous soil series classification using machine learning. In our work, we have implemented
Bagging Classifier, Support Vector Machine, and k-Nearest Neighbour for soil classification and crop recommendation.
