Approximately a quarter of Turkey's population suffers from mineral deficiency, and seaweed, rich in minerals, offers a potential dietary solution. However, limited data and technological constraints hinder identifying natural seaweed distribution, especially in developing countries. A computational methodology based on prediction was developed to pinpoint marine habitats with minimal available data to address this. This study proposes a method using McHarg's overlay methodology to forecast marine life distribution and migration trends with limited reference. Modifying the Species Distribution Model (SDM) algorithm, utilizing rule-based prediction and ecological layers, facilitates the analysis of seaweed species distributions in Turkish marine habitats. It generates heat maps based on the algorithm indicating favorable areas for specific species. Fieldwork validated the accuracy of this method, particularly in predicting the occurrence of Cystoseira barbata in Fethiye. Consequently, this methodology holds promise for applications in landscape architecture, aiding habitat mapping, identifying potential development zones, conducting relevant area analyses, and optimizing environmental conditions for efficient landscape design.