In a context of increasing natural disasters and extreme climate events worldwide, the effective management of these crises becomes essential. Peru, with its diverse geography and vulnerable population, faces a growing threat of floods, forest fires, droughts and the El Niño Phenomenon due to factors such as climate change and urbanization. The purpose of this research is to explore how artificial intelligence (AI) can improve the accuracy in predicting climate events and natural disasters in Peru, identifying obstacles and opportunities in its application. Despite its potential, AI in disaster management faces challenges such as the limited availability of reliable historical data and the complexity of climate systems, but the importance of addressing these limitations is recognized. The research highlights the originality and value of using AI to strengthen the capacity for prediction and response to natural disasters in Peru, focusing on variable selection, data integration and real-time application. The results indicate that AI has significant potential to improve the accuracy of predicting natural disasters in Peru, despite limitations, highlighting its ability to process data in real time and provide early warnings. In conclusion, the research highlights the importance of effective disaster management in Peru and the crucial role of AI in this task, recognizing challenges and limitations, but emphasizing its potential to strengthen preparation and response to extreme climate events and natural disasters in Peru the country.