A computer-intensive process was performed to simulate 12,600 data sets each with n = 5,000 individuals from distinct pedigree structures to assess the effect of pedigree information on the sampling variance of heritability (h2) estimates. Pedigree structures were determined by varying the proportion of foundation animals (PF), percentage replacement rates for males (RM) and females (RF), and ratio of females to male (F2M). A 2(3) factorial design was modeled; levels of RM and RF were 10 and 20%, and levels of F2M were 10 and 20. For each of the eight cells, 60 foundation animals were simulated, each with 10 replicates. The required mating seasons (MS) to obtain the number of individuals was simulated based on PF and F2M. A REML algorithm was used to estimate h2 and its associated SE. The effect of all factors was analyzed in a regression model with linear and quadratic components for PF. An alternative model with MS replacing PF was also investigated. There was a non-monotonic association (P < .01) between PF and h2 SE. The minimum h2 SE occurred when PF ranged from 20 to 40%. Here, the proportion of first-generation progeny was near its maximum with rapid increases in the proportion of subsequent descendants. Among the class effects, F2M yielded the highest mean square (P < .001). When considering more than one MS, h2 SE was positively associated (P < .01) with RF and F2M and negatively associated with RM. Results suggest that h2 is most accurately estimated when there is performance information on many animals closely related to foundation animals.