Buildings' performance is a vital aspect of organizational activity which is affected by maintenance procedures and policies. Therefore, facility maintenance plays a crucial role in informing strategic decision making. This research proposes the use of key performance indicators (KPIs) to dynamically model and simulate the performance of the existing facilities. Further, it transforms the descriptive analytics into predictive and prescriptive analytics by assessing the robustness of plans and policies set and by predicting future outcomes, through analyzing of multiple scenarios. Moreover, the research highlights the effect of energy consumption on the operating costs, and how it affects the building performance. For instance, when decreasing energy consumption by 58%, the operating costs can decrease to 55%, taking into account that the operating costs include not only that of energy, but also the cost of materials consumed. Hence, the building performance should increase unless the deferred maintenance has not been completed yet. This paper is part of a research that aims at using System dynamics modeling to quantify the interrelationship and interdependence of KPIs which studies the performance of existing building from three aspects financially, physically and functionally, as it is potentially effective in analyzing how maintenance expenditures can be optimized to maintain the desired level of building performance as demonstrated by several simulation scenarios. All parameters and variables used are quantified in terms of cost and introduced in a dynamic model where the functionality of the KPIs is dependent on the availability of data from the buildings in use. The proposed approach helps facility management professionals not only in tracking the indicators, but also in quantifying and studying the correlation between them based on available information. This leads to enhancing facility management decisions, with measurable facility performance outcomes.