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Submarines are essential naval assets due to their difficulty in detection. Selecting appropriate equipment for mission efficiency is essential, and automating these tasks with a Decision Support System (DSS) is vital. Air Independent propulsion (AIP) is critical for covert submarine operations, allowing propulsion underwater without surfacing for oxygen. Choosing the right AIP system is challenging because it requires balancing operational efficiency, economic cost-effectiveness, and environmental consequences, all of which entail complex factors that are difficult to quantify or compare. The developed DSS is based on a two-stage Fuzzy Mamdani Model (FMM), applied to perform inference over a submarine AIP. Three reference values were obtained in the first stage to aid operational, economic, and environmental decision-making. In the second stage, these three values create a recommendation value using a percentage system selection. To prove its effectiveness, the DSS was used to evaluate four types of AIPs to establish the level of recommendation and the values of the subcategories in the initial phase. Experts from the Portuguese Navy (PoN) assisted with the system development by defining decision-making rules. The FMM offers advantages over traditional decision-making models by effectively managing vague and qualitative data, enabling reasoning that reflects expert judgment instead of relying on deterministic models. 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