Artificial Intelligence (AI) and Machine Learning (ML) are essential in tackling global challenges related to climate disaster management and earth resource management. AI-enabled systems analyse vast datasets for precise predictions of weather patterns, early warning systems for floods, hurricanes, and wildfires, and real-time decision-making during disaster response. The research aims to bridge technological advancements with ecological responsibility. This work explores the application of AI and ML technologies to predict, mitigate, and manage climate disasters while optimising the use of natural resources. ML algorithms enhance these capabilities by learning from historical data to improve accuracy and adaptability over time. AI and ML contribute to sustainable practices by monitoring and assessing the health of ecosystems with optimisation of agricultural productivity and managing water resources more efficiently. Advanced models identify patterns of deforestation, biodiversity loss, and resource depletion, offering actionable insights for policymakers and stakeholders. This study highlights the potential of AI and ML in fostering resilience against climate disasters and promoting sustainable development. It also addresses the challenges, such as data accessibility, ethical considerations, and the need for collaboration across sectors. These cutting-edge technologies can reduce environmental risks with the conservation of natural resources for a sustainable future.