IterativeImputer Evaluation
When imputing data, one is looking not to modify the true distribution of your data. So a way to test how good your imputation was is to make a test to contrast the true distribution of every feature that has been imputed vs the true (via KS test for example) distribution of the feature (prior imputing) if you can sate with a level. of confidence that your imputation preserved the distribution that would be a way.
Another way would be in case you have a supervised task, you can compare the performance of your model on each imputation technique. Like in the below's image from Scikit-learn documentation: