Since 2022, Fernanda Carlés has been working alongside the National University of Asunción to develop machine learning models for predicting AQI levels for UNA’s ten monitoring stations. This effort has resulted in high-performance machine learning models that offer air quality predictions for six- and 12-hour horizons with impressive accuracy rates of 91% and 86%, respectively. The goal of this project is to bring the predictive power of these machine learning models to the public. To achieve this, the project proposes the development of a user-friendly web application that offers real-time air quality forecasts with interactive visualizations and alerts. This application will utilize real-time data from existing monitoring stations in the Gran Asunción area, combined with validated machine learning models.