Monitoring technology trends is essential for the European Space Agency (ESA) to fulfill its mission of advancing Europe's space capabilities. Yet, in a rapidly evolving ecosystem where information is scattered across various databases and formats this is no easy task. In this study we present a novel approach to predict and track the technologies related to ESA R&D studies, based on the ESA Technology Tree. Leveraging pre-trained Large Language Models (LLMs) from OpenAI and Mistral AI, we demonstrate how to enrich a database with technology-related information, providing fresh insight into technology trends.