  We study the substructure content of the strong gravitational lens
RXJ1131-1231 through a forward modelling approach that relies on generating an
extensive suite of realistic simulations. We use a semi-analytic merger tree
prescription that allows us to stochastically generate substructure populations
whose properties depend on the dark matter particle mass. These synthetic halos
are then used as lenses to produce realistic mock images that have the same
features, e.g. luminous arcs, quasar positions, instrumental noise and PSF, as
the data. We then analyse the data and the simulations in the same way with
summary statistics that are sensitive to the signal being targeted and are able
to constrain models of dark matter statistically using Approximate Bayesian
Computing (ABC) techniques. In this work, we focus on the thermal relic mass
estimate and fix the semi-analytic descriptions of the substructure evolution
based on recent literature. We are able, based on the HST data for
RXJ1131-1231, to rule out a warm dark matter thermal relic mass below 2 keV at
the 2$\sigma$ confidence level.
