Algae growth on historical building surfaces poses aesthetic and structural challenges. Quagliarini’s modified Avrami’s model establishes a relationship between substrate temperature, relative humidity (RH), and algae growth under controlled conditions. However, when applied to real weather datasets, it fails to directly capture the influence of dynamic climatic factors. This study bridges this gap by analysing the relationship between temperature, RH, and rainfall on algae risk. Using Brussels climate data, a 1-D HAM simulation was conducted on two historical building types across eight orientations and four wall factors, with algae risk assessed via the modified Avrami’s model. Key findings include: (1) algae growth follows a sigmoidal pattern, peaking between Years 2–4, with higher risk on S, SW, and W façades; (2) growth becomes significant when temperatures exceed 12 ℃ and RH surpasses 70–75%, with peaks in June and July; (3) 60–85% of growth occurs 24–48 h after rainfall; (4) a risk prediction model was developed to assist design decisions and initial risk screening. These findings enable preliminary algae risk assessments based on climate conditions, assisting design decisions and initial risk screening.