High-precision predictions in BSM models require calculations at the
loop-level and thus a renormalization of (some of) the BSM parameter.
Here many choices for the renormalization scheme (RS) are possible.
A given RS can be well suited
to yield ``stable'' and ``well behaved'' higher-order corrections in one
part of the BSM parameter space, but can fail completely in other
parts. The latter may not even be noticed numerically if an isolated
parameter point is investigated.
Here we review a new method for choosing a ``well behaved'' RS.
We demonstrate the
feasibility of our new method in the chargino/neutralino sector of the
Minimal Supersymmetric Standard Model (MSSM), but stress the general
applicability of our method to all types of BSM models.