Bubble point pressure is a critical pressure-volume-temperature property of reservoir fluid, which plays an important role in almost all tasks involved in reservoir and production engineering. In this study, three worldwide empirical formulas, presented by several researchers, were employed to estimate bubble point pressure from the gas specific gravity, temperature, stock-tank oil gravity, and solution gas oil ratio. Consequently, a power law combination of the aforementioned equations was designed to enhance the accuracy of target prediction. A hybrid genetic algorithm-pattern search tool was utilized to extract the optimal coefficients of power law equation. This methodology was applied to 361 worldwide data points. The results showed that by a little computation, using a genetic integration of empirical formulas, more reliable results could be achieved.