Technical Abstract: Variance components for a threshold sire-maternal grandsire (MGS) model were estimated from subsets of the US calving ease (CE) database which includes over 10 million calving records with CE scored 1 (no problem) to 5 (extreme difficulty). Selected records included an identified MGS, and sire and MGS among the 2601 most frequently appearing bulls. The data were further restricted by requiring 20 records in each herd year. Five mutually exclusive sample datasets of approximately 200,000 records each were created based on herd code. The model included random herd-year, sire, MGS, and residual effects and fixed year-season, parity-sex, and birth year of sire and MGS effects. Fewer than 50 iterations were required to reach convergence. The (co)variance component estimates from the five replicates were quite similar. The set of estimates (herd-year variance = 0.438, sire variance = 0.022, MGS variance = 0.016, sire-MGS covariance = 0.009) that yielded among the highest heritabilities (direct heritability = .086, maternal heritability = .048) and a correlation of direct and maternal effects near the mean (direct-maternal correlation = -.12) was selected for use in the implementation of a sire-MGS model for calving ease.