The Logistic Regression Model (LRM) is successful in many fields due to its capability of predicting and describing the relationship between binary response variables and one or more independent variables. However, the prediction results of this model are still not accurate enough due to error terms, regardless of their existence in the model. To overcome this problem and, at the same time, produce more accurate and efficient predictive model values, the bootstrap approach was proposed. Unfortunately, this approach did not receive any attention, especially for this model. This study aims to introduce the bootstrap approach to LRM and investigate the performance of the proposed models using data on wound healing using jellyfish collagen. The results revealed that the proposed model generated smaller values of MSE and RMSE, as well as shorter confidence intervals, compared with the existing LRM. These results proved that the proposed model could produce an estimated value that is more ac.....

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