When being outsourced from big companies, the Facility Management market reached another level of scale. In 2012, Thales group entrusted one company to cover all its Facility Management (FM) areas but with separated Service Level Agreements (SLAs) per areas and per sites. Most of the FM costs, circa 80%, cover employees' salaries. As a customer, Thales' goal is not to pay the cheapest price but to pay the adequate price. Since service offering impacts this price, it is crucial to identify the main characteristics for each SLA. In this paper, we address the problem of predicting the price of Facility Management SLAs using the data from the Thales group's sites in France. To this end, we applied multi-variable linear regression and qualified the obtained results. While some results follow the intuition one can have, others were less expected.