The adoption of electric boats faces challenges due to range anxiety. This study addresses this challenge by optimizing the allocation of slow and fast chargers for public electric boat charging stations. A mixed-integer linear programming model was developed to minimize charging infrastructure and electricity costs while meeting the demand of each participating marina in Stockholm, Sweden. The model identified three distinct categories of stations based on the optimal charger allocation: stations prioritizing fast chargers (e.g., Sickla station with 13 fast and 8 slow chargers for 208 boats), stations prioritizing slow chargers (e.g., Kungsholmen station with 2 slow and 3 fast chargers for 50 boats), and stations with an equal number of both charger types (Äppelviken station with 2 each for 25 boats). This study found out that all stations will achieve financial viability within seven years, indicating a promising return on investment. This study also proposes a novel way for optimizing charger allocation in electric boat charging infrastructure, promoting wider electric boat adoption.