Marine species are subject to anthropogenic impacts, such as noise pollution, marine litter, and direct impact collisions. While there are efforts in the marine community and crowd-sourcing to report the occurrence of marine species, not enough projects explore the prediction of where such animals may be. This dissertation analyzes the state of the art in species distribution model ing (SDM) systems, capable of reporting and predicting marine biodiversity. The proposal implements the algorithms for predicting species through publicly avail able repositories of data, provides means to ease the upload and management of occurrence points as well as methods for prediction analysis. A web-based user interface is proposed using Ecological Niche Modelling (ENM) as an automated alerting mechanism towards ecological awareness. Performed user studies evaluate marine biodiversity concerns from fisherman and whale-watching sea-vessels, assessing attitudes, threats, values, and motiva tion of both samples. Further, biologists and experts on ENMs will evaluate the workflow and interface, reviewing the proposal’s potential to enable ecologists to create solutions for their custom problems using simple protocols without the need for any third-party entities and extensive knowledge in programming.