Passage planning and monitoring are two essential and mentally demanding tasks in maritime navigation. Ships are facing higher risk of running aground when they take a route for the first time or are to stray from their planned route, and of collision when navigating areas of increased maritime traffic. Many researchers have studied methods to create traffic heat maps, extract predominant routes, and generate ship trajectories, however, we lack a dynamic solution that will be readily available to mariners on the bridge and to autonomous vessels. The Roads of the Sea project aims to address the issue of non-uniform marine navigational schemes through a passage planning and prediction system that can support optimal marine navigation. This project aims to assist users, both humans and machines, in safely traversing the seas by providing routes customized to the own ship, based on those that have been previously taken by ships with similar characteristics, and by predicting other ships’ trajectories. This paper presents an initial implementation of the project by constructing a custom grid-like model representative of maritime travel and a safe route suggestion algorithm. These features are developed by filtering and analyzing Automatic Identification System (AIS) and chart data. The AIS data relays important vessel information including dimensions, headings, and locations that we utilize to establish the routes certain ships take. The model utilizes the A* pathfinding algorithm to suggest routes by allocating weights to each grid cell for the requested ship’s characteristics and traversing movement of least cost.