  For many particle collider searches for physics beyond the Standard Model in
final states with jets and missing transverse momentum, events from QCD
multi-jet processes are an important and challenging background contribution.
The CMS and ATLAS experiments have previously developed data-driven methods
designed to succeed where Monte Carlo methods suffer large theoretical and
experimental uncertainties. One such method is Rebalance and Smear (R&S), which
predicts QCD backgrounds by applying a series of folding and unfolding
techniques to data control regions. A top-to-bottom description of the R&S
method is presented, along with a discussion of its applicability and
limitations. A software application is provided that performs the R\&S method
using public, non-proprietary tools, interfacing with data sets produced by
Delphes3. In general, the method is suitable for predicting multi-jet
backgrounds in searches for stable non-detectable particles, such as dark
matter candidates. A case study is carried out in simulated events of
proton-proton collisions at 14 TeV in the context of a potential search for
Higgsino dark matter produced in the decay products of supersymmetric quark
partners. Sources of potential bias are explored and prescriptions for
evaluating systematic uncertainties are suggested.
