An improved algorithm that optimizes Pease-Anthony type venturi scrubber performance is presented in this work. This approach predicts the minimum pressure drop needed to achieve the desired collection efficiency by optimizing key operating and design parameters such as liquid-to-gas ratio, throat gas velocity, number of nozzles, nozzle diameter, and throat aspect ratio. A detailed assessment of four established pressure drop models and an extension of two of the models by providing an empirical algorithm to give better prediction of pressure drop in the venturi throat have been conducted by validating them with experimental data. This optimization algorithm provides a stepwise, effective, and accurate approach to optimizing both existing and new scrubbers.