  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.
