In this paper, we estimate foam parameters and investigate foam behavior for a given range of water saturation using two local equilibrium foam models: the population balance and the Pc*. Our method uses an optimization algorithm to estimate foam model parameters by matching foam measured pressure gradient from steady-state coreflood experiments. We calculate the effective foam viscosity and the water fractional flow using experimental data and we then compare lab data against results obtained with the matched foam models to verify the foam parameters. Other variables, such as the foam texture and foam relative permeability are used to further investigate the behavior of the foam during each experiment. We propose an improvement to the Pc* model with a better match in high quality regime by assuming resistance factor and critical water saturation is a linear function of pressure gradient. Results show that the parameter estimation method coupled with an optimization algorithm successfully matches the experimental data using both foam models. In the population balance, we observe different values of the foam effective viscosity for each pressure gradient due to variations of the foam texture and shear thinning viscosity effect. The Pc* model presents a constant effective viscosity for each pressure gradient; we propose the use of resistance factor and critical water saturation as a linear function of pressure to improve the match in the high quality regime, when applicable. Foam has been successfully used in the oil industry for conformance and mobility control in gas injection processes. The efficiency of a foam injection project must be assessed by means of numerical models. Although there are several foam flow models in the literature, the prediction of foam behavior is an important issue that needs further investigation.