Asthma prediction is a crucial area of medical research, with the goal of developing models that can predict asthma onset, exacerbation, and management outcomes. Leveraging deep learning for this task offers promising possibilities due to its ability to handle large, complex datasets, such as medical records, sensor data, genetic information, and environmental data. Deep learning can help discover patterns that may not be visible through traditional statistical methods, leading to early detection and better management of asthma.Asthma Prediction using Deep Learning provide exciting opportunities to tackle real-world healthcare challenges by leveraging cutting-edge AI techniques. These projects span multiple areas such as time-series analysis, EHR data integration, genomic data modeling, environmental monitoring, and explainability, offering significant potential for improving asthma diagnosis, prediction, and management. Each project focuses on different aspects of asthma prediction, with the overarching goal of developing accurate, interpretable, and clinically useful deep learning models.