In the Trading Agent Competition Ad Auctions Game, agents compete to sell products by bidding to have their ads shown in a search engine's sponsored search results. We report on the winning agent from the first (2009) competition, TacTex. TacTex operates by estimating the full game state from limited information, using these estimates to make predictions, and then optimizing its actions (daily bids, ads, and spending limits) with respect to these predictions. We present a full description of TacTex along with analysis of its performance in both the competition and controlled experiments. Categories and Subject Descriptors I.2 [Computing Methods]: Artificial Intelligence General Terms Algorithms, Experimentation, Economics Keywords trading agents, sponsored search, ad auctions