Method R estimates of heritability (h2) and associated confidence intervals (CI) were obtained from simulated data using a single trait, direct effects, full animal model, with 50% subsampling. Five hundred data sets were simulated for each of five levels of h2 (.10, .20, .30, .40, and .50) and two types of pedigree structure (random pedigree structure [N = 2,000] that varied over simulations, or the pedigree structure from a real data set [N = 2,644] that was constant for all simulations). The first 10, 20, and all 50 h2 estimates were used to obtain 80, 90, 95, and 99% CI for each data set. The variance of h2 estimates within data sets approximated the sampling variance of the h2 estimates. The Box-Cox transformation was used to normalize the distribution of estimates from each data set. Confidence intervals were computed on the transformed scale as CI = mu +/- (T x sigma), where mu and sigma = the mean and SD of the N transformed h2 estimates, respectively, and T = the critical value from the T distribution for a 1-alpha CI, with df = N-1. Upper and lower CI bounds were converted back to the original scale by reversing the transformation. The percentages of CI containing the true h2 value, pooled across all levels of h2, types of pedigree, and number of estimates used to obtain CI, for 80, 90, 95, and 99% CI were 81.14, 90.96, 95.27, and 98.76%, respectively. These results suggested that Method R h2 estimates can be used to obtain reliable CI.