While visual inspections by specialists play a crucial role in assessing façade degradation in heritage buildings, such methods often lack standardized or quantifiable metrics, which can hinder objective comparison and long-term monitoring. This study integrates hyperspectral imaging (HSI) and hygrothermal (HAM) simulations to improve algae growth predictions. Using the Castle of Horst as a case study, HSI-derived Normalized Difference Vegetation Index (NDVI) maps were compared with HAM-based simulations using a modified Avrami’s model. Results show that while the model captures general trends in material properties and height-dependent growth, it overestimates algae coverage and fails to reflect orientation sensitivity. Overestimated wind-driven rain at lower walls contributes to this discrepancy, highlighting the need for refined wall factor values. This research is a contribution to advances in algae growth modelling and degradation assessment, which is an important information regarding heritage conservation under climate change.