Rutting has been considered as the most serious distresses in flexible pavements for many years. Flow number
is an explanatory index for the evaluation of rutting potential of asphalt mixtures. In this study, a promising
variant of genetic programming, namely gene expression programming (GEP) is utilized to predict the flow
number of dense asphalt-aggregate mixtures. The proposed constitutive models relate the flow number of
Marshall specimens to the coarse and fine aggregate contents, percentage of air voids, percentage of voids in
mineral aggregate, Marshall stability and flow. Different correlations were developed using different
combinations of the influencing parameters. The comprehensive experimental database used for the
development of the correlations was established upon a series of uniaxial dynamic creep tests conducted in this
study. Relative importance values of various predictor variables were calculated to determine their contributions
to the flow number prediction. A multiple least squares regression (MLSR) analysis was performed using the
same variables and data sets to benchmark the GEP models. For more verification, a subsequent parametric
study was carried out and the trends of the results were confirmed with the results of previous studies. The
results indicate that the proposed correlations are effectively capable of evaluating the flow number of asphalt
mixtures. The GEP-based formulas are simple, straightforward and particularly valuable for providing an
analysis tool accessible to practicing engineers.