Forest fires, exacerbated by the increasing frequency and intensity of extreme weather events, remain a pressing concern. Developing effective forest fire emergency management systems is paramount to mitigate the impacts of future events. The SAFERS project (Structured Approaches for Forest fire Emergencies in Resilient Societies) addresses this challenge by proposing a modular and comprehensive Emergency Management System (EMS) encompassing all phases of the emergency management cycle. The main backbone of SAFERS is composed of Intelligent Services (ISs) linked with a web-based platform allowing data visualization and end-user interactions. These services integrate diverse data sources, including Earth Observation data, meteorological forecasts, and crowdsourced information. Through advanced technologies such as Artificial Intelligence (AI) algorithms, the ISs enable early warnings, rapid fire detection, propagation prediction, postevent assessment, and monitoring of soil recovery. This work focuses on these services and on the methodologies applied within SAFERS to enhance decision-making capabilities, facilitate effective response strategies, and promote resilience in the face of forest fire emergencies.