Agriculture is a non-technical sector where in technology can be incorporated for the betterment. Agricultural technology needs to be quick in implementation and easy in adoption. Farmers usually follow a method called crop mutation after every consequent crop yield. The crop mutation allows the soil to regain the minerals that were used by the crop previously and use the left over minerals for cultivating the new crop. To know if the soil has reached the point where it is unfit to yield the particular crop, farmer has to experience a loss in yield. One financial year for a farmer is very crucial to accept the loss. This paper implements a that would help in maintaining the soil fertility consistently. This method is traditionally implemented in many countries where the change in crop is done after a loss in yield for cultivating the same crop continuously. There are three soil parameters that come into consideration when we have to predict the soil quality. This method suggests the solution for the above stated problem using Machine Learning Techniques. This paper suggests a software enabled solution considering crucial soil parameters and soil factors to predict the soil quality.