In this study, smoothing and scaling approaches are compared for estimating subscore-to-composite scaling results involving composites computed as rounded and weighted combinations of subscores. The considered smoothing and scaling approaches included those based on raw data, on smoothing the bivariate distribution of the subscores, on smoothing the bivariate distribution of the subscore and weighted composite, and two weighted averages of the raw and smoothed marginal distributions. Results from simulations showed that the approaches differed in terms of their estimation accuracy for scaling situations with smaller and larger sample sizes, and on weighted composite distributions of varied complexity.