Routing in Delay Tolerant Networks (DTNs) can benefit from the fact that most real life DTN, especially in the context of people-centric networks (e.g. Pocket Switching Networks (PSNs)), exhibit some sort of periodicity in their mobility patterns. For example, public transportation networks follow periodic schedules. Even most individuals have fairly repetitive movement patterns, for example, driving to and from work at approximately the same time every day. This paper proposes a BayesiaLab tool based DTN routing framework that adopts a methodical approach for computing the routing metrics by utilizing the network parameters that capture the periodic behavior of DTN nodes.