A recommender system is a type of system which performs filtering of information and produces useful inferences. In Indian classical music, a raga is a series of swaras (musical notes) in a particular order. Many musicians of Indian classical music follow the practice of transitioning from one raga to another while singing. The source raga and the destination ragas resulting from the transition have relationships with each other. In this research article, Carnatic music which is a form of Indian classical music, is taken as an application and a recommender system is proposed using methodologies related to Artificial Intelligence and other domains, like First Order Logic (FOL), gauging using distance measures and chi-square distribution in order to determine the destination ragas and their relationships with the source raga. Among the ragas which can be reached from a particular raga by raga-to-raga transition, the best-fit destination raga(s) are found out using distance measures. As an analysis of the gap between the source and destination ragas, one-way chi-square distribution is deployed. The hypothesis is tested for accuracy using confusion matrix. The application of this recommender system is to provide a list of all possible destination ragas reachable from an input source raga, thereby proving to be of great use to musicians, Music Information Retrieval (MIR) systems, automatic music creation software etc.