The prediction of the time of default in a credit risk setting via survival analysis needs to take a high censoring rate into account. This rate is due to the fact that default does not occur for the majority of debtors. Mixture cure models allow the part of the loan population that is unsusceptible to default to be modelled, distinct from time of default for the susceptible population. In this paper, we extend the mixture cure model to include time-varying covariates. We illustrate the method via simulations and by incorporating macro-economic factors as predictors for an actual bank data set.