Abstract Petroleum engineers must accurately determine bubble point pressure (Pb) to optimize oil field development from discovery to abandonment. Errors in predicting this parameter can lead to inaccurate reservoir and production estimates. To enhance Pb predictions, A total of experimentally measured 1,161 oil samples from Egyptian oil reservoirs (604 heavy oil and 557 light oil) were used for regression analysis. In contrast, 232 datasets were used to support the artificial neural network model.