ANN models are data-dependent models that can predict the target values from a set of input parameters without considering the physical laws governing the relationship between input and output parameters. In the present study, ANN models are employed to calculate SPT-N values as a function of the grain size distribution data (% of gravel, sand, silt, and clay) of each soil layer from different boreholes as well as the effective overburden pressure at the corresponding depth. The soil investigation data are obtained from boreholes constructed in the Kalpasar dam site location in the state of Gujarat, India. Comparison of the N-values calculated from the ANN models to that measured in the field is carried out to examine the feasibility of using such models to derive the N-values. Also, the proximity of the derived N-values to either of the observed N-values is noted. Such a method if practical can enable deriving N-values for soil strata/locations where SPT shows refusal or SPT test cannot be carried out. Apart from this, important soil properties like shear strength parameters, modulus of soil, etc. can be evaluated from N-values. Thus, N-values derived using such models can enable further calculation of such important soil parameters from established correlations. However, ANN models may be adopted as an ancillary tool to derive the N-values and not as a replacement for field tests.