Although finite-difference time-domain (FDTD) simulations are extensively used in acoustics, studies assessing the reliability and the accuracy of the implemented method are scarce. Moreover, the operational validity of a simulation method is context-dependent. Motivated by the context of head-related transfer function (HRTF) prediction, this work presents a verification procedure for FDTD-simulated HRTFs from a simplified model of a human head and torso which comprises two spheres and is known as the snowman model. The analytic solution required by the code verification is computed with the multipole reexpansion technique and used to compute convergence rate estimates. A solution verification process follows in which asymptotic predictions are computed. Results from the code verification show scattered convergence rates which attained the expected first-order accuracy at frequencies below 1 kHz when a linear regression model was used as the estimation procedure. Results from the solution verification show that the asymptotic predictions are accurate up to 10 kHz, after which bias is observed. Assessing the accuracy of the employed solution verification procedure revealed that the absolute difference between the $\log $-magnitude of the asymptotic predictions and this of the analytic solution is within 1 dB up to 11589 Hz across the HRTF directions considered.