In this paper, the authors propose data pooling techniques that allow designers to extract statistical measures of fatigue resistance and its variability from several sets of fatigue data for a given material. As the number of fatigue data banks and the exchanges of fatigue data continue to increase, these techniques will enable designers to obtain fatigue statistics from pooling of data sets that could not be obtained from any one of the invariably small sets of data. When stress-life fatigue data are plotted on log-log scales, the Basquin relationship, a simple inclined straight line, is used to fit the data. When strain-life fatigue data are plotted on log-log scales, two inclined lines are used to fit the data. Elastic and plastic strain fatigue data are plotted based on Basquin and Coffin-Manson relationships, respectively. Fatigue data sets from the same population are pooled together based on the variance, slope, and intercept of the samples. Applications of the data fitting and pooling are presented using sample data sets. A probabilistic design concept is illustrated using pooled material data and arbitrary load histories.