We carried out numerical simulations of the conductivity of snow using microtomographic images. The full tensor of the effective thermal conductivity (keff) was computed from 30 three-dimensional images of the snow microstructure, spanning all types of seasonal snow. Only conduction through ice and interstitial air were considered. The obtained values are strongly correlated to snow density. The main cause for the slight scatter around the regression curve to snow density is the anisotropy of keff: the vertical component of keff of facetted crystals and depth hoar samples is up to 1.5 times larger than the horizontal component, while rounded grains sampled deeply in the snowpack exhibit the inverse behavior. Results of simulations neglecting the conduction in the interstitial air indicate that this phase plays a vital role in heat conduction through snow. The computed effective thermal conductivity is found to increase with decreasing temperature, mostly following the temperature dependency of the thermal conductivity of ice. The results are compared to experimental data obtained either with the needle-probe technique or using combined measurements of the vertical heat flux and the corresponding temperature gradient. Needle-probe measurements are systematically significantly lower than those from the two other techniques. The observed discrepancies between the three methods are investigated and briefly discussed.