The greedy algorithm for matroids is considered to be a key concept in combinatorial optimization. It gives optimal solutions to the problems which can be described by matroid independence structures. In this chapter, we present the theoretical foundation of the matroid greedy algorithm, and its application in feature selection, activity scheduling, and fairness-aware model design through detailed examples and real-world case studies in artificial intelligence (AI).