The article explores how to predict bids in Internet auctions using a Bayesian approach. They studied data from notebook auctions on a Korean auction site and found that there are more hidden bidders than visible ones. They also discovered that the number of remaining bidders decreases as the auction progresses, and larger bid amounts and time increments affect bidding behavior. The model developed in the study can help understand how brand popularity influences bidding in online auctions.