Farmers require different types of agricultural machinery at different stages of cultivation. As farmers cannot keep all the machinery, they need to hire machinery from other farmers or vendors. We study two problems related to agricultural machinery distribution. Our first problem deals with assigning a single machine to different farmers for a different time slot so that more farmers can get the service. We modify the first problem by including the cost with resources. This price reflects factors such as the distance between the farmer’s location and the machinery storage area, the urgency of the request, and the availability of alternative solutions. The basis of our approach is the development of algorithms specifically designed to solve machine distribution problems. The algorithm uses data analytics to evaluate farmers’ demands for the technology. Also, the proposed framework prioritizes demand based on their ability to be profitable and productive, considering factors such as location, crop type, and demand rate.