Improving building performance through reducing negative environmental impacts can be achieved by greening existing buildings (GEB), which is considered a very important sustainability process. Due to the risky and uncertain nature of the process of GEB, a growing amount of attention should be given to eliminating the effects of risks on GEB. This research aims to identify most expected risk factors related to GEB, as well as to evaluate their effects through calculating risk factor characteristics, such as risk factor presence (RFP), impact on the GEB process (IGEB), and impact on building performance in the long run (IBP), as new indices describe these risks. Sixty-six risk factors were categorized in seven risk groups related to the economic aspect, social aspect, environmental aspect, managerial aspect, sustainability operation, sustainable design, and renovation. Moreover, a fuzzy model for risk analysis was developed to combine the multi-effects of the aforementioned three risk factor characteristics in one index representing the risk factors’ overall importance. The model was applied and verified for data collected in Saudi Arabia. The results of this study showed that the most important risk group is the greening process of environmental control, while the least important is the greening process of renovation and construction. Using the proposed model improved the results of evaluating risks affecting GEB through merging the multi-effects of risk factor characteristics. The results and analysis proved that the most important key risk factors were environmental in nature. An intricate relationship of the impacts on the GEB process and building performance with the overall importance of the risk factors was clearly found. The decision makers who deal with greening projects in Saudi Arabia should be aware of the key risks identified in this study. The proposed methodology and model can be easily applied to other countries to help decision makers in evaluating their GEB projects, as well as comparing more greening projects based on risk analysis.