The established approach to calculating the cause-deleted life expectancy in a competing risks framework is to simply remove the deaths caused by the risks in question from the life table. However, this is clearly untenable, since the lack of presence of a cause of death will take time to be fully realized. To correct for this oversimplification, we propose a multivariate cure-of-cause model that can incorporate probability distributions for the cures of multiple causes of death over time as a means to more accurately predict the overall increase in life expectancy that would ensue at each age. Note that our models are decidedly distinct from what is commonly understood as “cure modeling” in the survival literature.The theoretical results are applied to a real data set involving both diabetes and HIV-related deaths. Future work might include generalizing the model even further to account for dependence between the various cure-of-cause distributions.