The shipping industry contributes significantly to the global greenhouse gas emissions due to the use of cheap fossil fuels. The booming cruise ship industry is forced to reduce the emitted greenhouse gases and emission of carbon dioxide to be able to access remote areas with higher restrictions and to comply with upcoming regulations. Fuel cells are a promising alternative to conventional diesel-powered systems to reduce the emissions. Next to the physical implementation, fuel cells have additional operational limiting factors, which have to be matched with the power demand. Compared to conventional combustion engines, longer start-up times and a lower dynamic response ability can be expected. Typically, the energy demand is estimated for all electric power consumers with the load balance approach in the conceptual design phase. The actual power demand is calculated based on the absorbed power and additional predefined factors for specific conditions. This conflicts with the dynamic power demand of cruise ships in various operational conditions. This thesis discusses the used bottom-up approach for such an improved prediction of the total power and energy demand of an expedition cruise vessel for the early design stages. The focus is on identifying the peak loads and load changes under consideration of the passenger behaviour, environmental and operational conditions on the basis of predefined typical days of operations. The dynamic power demand is predicted for the different propulsion, auxiliary and hotel systems, as identified and grouped in the system breakdown. This is done by using separate prediction models for the defined groups of systems and electrical components. The required energy per day is calculated directly from a time-domain integration of the power prediction. The demand for a whole operational profile is obtained by adding different typical operational days. The highest power is required by the main propulsion in sailing mode. However, expedition cruise ships often operate at lower speeds below the design conditions resulting in a considerably lower load. The maximum load of the hotel systems always appears in the morning, when all passengers are on board and several components ramp up from the lower night mode. Comparing the total power demand shows that the load changes caused by the hotel systems gets smaller in relation to the changes within the propulsion system as soon as the speed varies. In port condition, the relatively constant auxiliary load, including the hotel systems, remains and describes the baseload throughout the day. Generally, the dynamic prediction clearly shows the potential to better estimate the required power and energy, if varying operational conditions are considered. The method supports a well-founded decision on the power supply configuration, if it comes to hybrid systems including different power supply components and their operational characteristics. A multi-criteria decision analysis on the power supply side can build up on the required energy and power demand of a certain part load. The required fuel cell size can be quantified based on the estimated maximal load and the fuel tanks by considering the predicted energy demand of the specific group of systems.