A shortage of vessels at a port can significantly impact cargo and trade flow. Businesses can predict when and how vessels will be available by understanding the factors that influence vessel availability at a port. This knowledge can help minimize the impact of vessel shortages and ensure that cargo is delivered to its destination as quickly and efficiently as possible. Following an initial literature review of available methods, the thesis proposes a method to predict the availability of the vessels at a port specific to particular types of cargo. The technique first predicts the arrival port for all the vessels, and then it calculates the Estimated Time of Arrival (ETA) at the expected port. For the prediction, the Extreme Gradient Boosting (XGBoost) model has been trained on different vessel types specifically for cargo, and for the ETA routing engine of a collaborating company of the thesis Maritime Optima AS (MO) has been used. The thesis also explores the commercial applicability of the proposed solution in different shipping industry segments by drawing on feedback from industry experts to identify opportunities as well as limitations of the proposed technique. The thesis is completed in partnership with the marine firm Maritime Optima AS (MO), which offers all of the preliminary data necessary to complete the work in the thesis. Furthermore, MO has provided access to the shipping experts as required at various phases of the thesis for confirmation and validation of the results developed as part of this thesis.