The increasing number of experimental data, accurate thermodynamic and reaction rate parameters drive the extension, revision, and update of large size kinetic mechanisms. Despite these detailed mechanisms (i.e. the models) generally allow good predictive capabilities, their management and update are critical. The usual validation procedure of a kinetic scheme consists in graphically comparing numerical simulations with the widest set of experimental data, with the goal of proving the model predictive capabilities over a broad range of temperature, pressure, and dilution conditions. At every iteration the model needs to be automatically evaluated through a quantitative methodology, without relying upon a standard graphical visualization. This work aims at proposing a method, named Curve Matching (CM), to evaluate the agreement between models and experimental data. The approach relies on the transformation of discrete experimental data and the relative numerical predictions in two different continuous functions. In this way, CM allows not only to compare the errors (i.e. the differences between the experimental and calculated values), but also the shapes of the measured and numerical curves (i.e. their first derivatives) and possible shifts along the x-axis. These features allow to overcome the limitations of Sum of Squared Error based methods. The present approach is discussed by means of a few models/experiment comparisons in ideal reactors and laminar flames. Due to the large number of both experimental data and kinetic mechanisms available in the literature, n-heptane was selected as the test fuel. (C) 2016 Published by Elsevier Inc. on behalf of The Combustion Institute.