This paper advances the collection of statistical methods known as response surface methods as an effective experimental approach for describing and comparing the tool life performance capabilities of metalcutting tools. Example applications presented demonstrate the versatility of the power family of transformations considered by Box and Cox (1964) in modeling tool life behavior as revealed using simple response surface designs. A comparative analysis illustrates a method to gauge the statistical significance of differences in tool life estimates computed from response surface models. Routine use of these methods in experimental tool testing is supported by their ability to produce reliable relative performance representations of competing tools in field applications.