In observational studies where the compared groups may be imbalanced in  terms of significant prognostic factors related to time-to-event  outcomes, traditional methods like the Kaplan-Meier (KM) function might  not align with multivariable regression models. To address this, we  introduce a new R package, “AdjKMCIF”, and a corresponding R shiny  application. This tool allows for the estimation of covariate-adjusted  KM functions and CIFs using the Cox and Fine-Gray regression models. The  package also integrates the Gail and Byar method, the Storer method for  stratified models, and the bootstrap method for confidence interval  estimation.