  This paper presents a novel approach to estimate the Standard Model
backgrounds based on modifying Monte Carlo predictions within their systematic
uncertainties. The improved background model is obtained by altering the
original predictions with successively more complex correction functions in
signal-free control selections. Statistical tests indicate when sufficient
compatibility with data is reached. In this way, systematic effects are
absorbed into the new background model. The same correction is then applied on
the Monte Carlo prediction in the signal region. Comparing this method to other
background estimation techniques shows improvements with respect to statistical
and systematical uncertainties. The proposed method can also be applied in
other fields beyond high energy physics.
