Purpose: There are several methods to predict organization bankruptcy; each of them has different accuracy. Another considerable note in investigating organization bankruptcy is the data considered for the study. The goal of this study is to determine which model is the most accurate in predicting organization bankruptcy. Research methodology: In this study, the initial data were used to compare predicting Monte Carlo processes that simulate bankruptcy models to compare models and results more accurately. Simulated data coefficient modification of Mckee, CA-SCORE, Springate, Zmijewski, Shirata, and Altman methods were implemented in some healthy and bankrupt organizations. After that, the results of each modified model were considered to determine the predicting bankruptcy accuracy. Results: Using the final Mckee's method, predicting organization bankruptcy was done in an organization and the results show that the given organization is on a trend of bankruptcy in 2025. Limitations: This research was only described in knowledge-based organizations. Contribution: The Mckee genetic method is more accurate than other methods. Also, modifying coefficient and by using simulated data shows that CA-SCORE and Shirata methods are not able to predict the organization's bankruptcy by using simulated data.