  We present a new methodology to discriminate between light and heavy
ultra-high energy cosmic-ray primaries on an event-by-event basis using
information from the radio detection of extensive air showers at MHz
frequencies. Similarly to other methods to determine primary cosmic ray
composition, the one presented here is based on comparisons between detected
radio signals and Monte Carlo simulations for multiple primary cosmic ray
compositions. Unlike other methods that first reconstruct the depth of maximum
shower development $X_{\rm max}$ to relate it to the nature of the primaries,
we instead infer the cosmic-ray composition directly. The method is most
effective in the case of inclined showers that arrive at large zenith angles
with respect to the vertical to the ground, where methods based on the
determination of $X_{\rm max}$ lose accuracy. We show that a discrimination
efficiency between 65% and 80% can be reached for zenith angles $\theta \gtrsim
60^{\circ}$, even when typical uncertainties in radio detection are taken into
account, including shower energy uncertainty. Our methodology could in
principle be applied in large and sparse radio arrays, designed with the large
radio footprint of inclined showers in mind, to significantly increase the
statistics of ultra-high energy cosmic-ray composition studies.
