Felix Academic Publications International Journal of Innovative Trends in Engineering Science and Technology 3139-6887 1 3 2026 11 07 Landslide Likelihood Detection using Machine Learning Algorithms 126 130 10.5281/zenodo.24037635 eng CH. Swapna Priya vignan's Institute of Information and Technology Naga Mahesh Kavuri vignan's Institute of Information and Technology Chandan Srinivas Etakaati vignan's Institute of Information and Technology Nishitha Bellakonda vignan's Institute of Information and Technology Kavitha Netela vignan's Institute of Information and Technology Siva Rama Krishna Kuda vignan's Institute of Information and Technology IJITEST-2026-028 10.5281/zenodo.24037635 2026 11 01 2026 11 07 Landslides are natural disasters that can cause significant damage to infrastructure, the environment, and human lives. Detecting landslides in a timely and accurate manner is critical for minimizing their impact. This project focuses on developing a landslide detection system using advanced technologies such as machine learning, remote sensing, and IoT. By integrating geological data, weather conditions, and real-time sensor inputs, the system aims to identify potential landslide-prone areas and provide early warnings. The proposed approach leverages predictive modelling to analyse patterns and correlations in large datasets, ensuring reliable and efficient detection. This solution can assist authorities in disaster management and help communities prepare for and mitigate the risks associated with landslides.