Manufacturers must frequently predict the number of future field failures for a product using past field-failure data, especially when an unanticipated failure mode is discovered in the field. Such predictions are needed to quantify future warranty costs and ensure a sufficient number of spare parts will be available to quickly repair failed units. In extreme cases, failure predictions are also needed to decide whether a recall is warranted and, if so, which segments of the product population must be recalled -- such as the units built during a specified period of time or those produced in a particular plant. Using an example of a fictitious company dealing with a failed part, this article will describe statistical methods for making these predictions.