Different service providers compete to win highly valued IT service contracts in a lengthy tender bidding process. These multimillion-dollar deals are complex in both solution design and service delivery. A successful bidding outcome does not solely depend on pricing. Hence, we experiment on a selection of deal factors that play critical roles in winning a deal. In this paper, we describe two machine learning models that use structured data to predict the bidding outcome of sales opportunities.