In agriculture, soil is a vital element that decides the quality and yield of agricultural produce. Soil consists of various nutrients such as nitrogen (N), phosphorous (P), potassium (K), the potential of hydrogen (pH), and water content. Nitrogen is responsible for building chlorophyll, which helps produce proteins and thus directly contributes to plant growth and development. Phosphorous is needed to develop root systems and flowers, whereas potassium helps increase disease resistance. Each of these play a role in crop cultivation. Thus, in this research paper, considering the fact that soil health will provide farmers with the best selection of crops that are compatible with their farm’s soil nutrients, we propose an algorithm for recommending a set of suitable crops based on various soil attributes. These soil nutrients can be collected in real-time using soil sensors, such as N, P, K, and pH, and humidity sensors. They can be deployed in farms where the cultivation takes place. These sensor readings would then be transferred to the blockchain layer, thereby validating the data and ensuring it is tamper-proof and evident. The crop recommendation model uses data from these sensors in real-time, increasing the results’ accuracy. The last stage leads us to display these results via a user dashboard, which helps the farmers to keep in check with their farm’s practices, and their sensor states from remote locations.