This paper compares parameterization techniques used for modeling the vertical profile of the ionosphere. In particular, comparisons of three-layer parameterizations driven by ionosonde data are performed. Quasi-parabolic, Chapman, and polynomial vertical profile models of the ionosphere are investigated. Optimization techniques applied at varying stages of the sensor output, ranging from direct inversion from the digital ionogram image to fitting to true height output for the estimation of parameters, are described. A Kalman-based filter is optionally used to track and filter the parameters. The performance of the various methods in producing the parameterized profile is analyzed through the comparison of predicted versus measured values of the F2 O-mode maximum observable frequency (MOF) on a 1250-km midlatitude oblique path. As a further benchmark, the monthly median model, FIRIC, is also used to generate oblique ionograms. It is found that three-layer parameterized models perform well and can increase prediction accuracy over the median model, with the ability to reduce the rms error in MOF estimation from 2.38 MHz to 0.83 MHz.