Multiple Imputation for Predictive Information

In practice, we will try to borrow information during the data collection process. The key is that we have to know that information for both respondents and non-response. We also try to do amputation: can we fill in the missing values of those who didn't provide that data? Imputation requires a model. How would you fit a model to fill in the potential outcome of those non-respondence?