Age-related Macular Degeneration (AMD) is the most common cause of severe vision loss in individuals over 50, primarily affecting central vision. In its early stages, AMD often presents no symptoms, making early detection and monitoring its progression essential. Managing AMD effectively requires close observation of neovascular activity, especially its response to anti-VEGF treatments. In this work, we present a predictive model that forecasts AMD progression 90 days in advance using a single Optical Coherence Tomography (OCT) B-scan. Our approach leverages advanced deep learning techniques and a novel latent matching model to improve the accuracy of disease state predictions and guide anti-VEGF treatment strategies.