  Reactive flows are important part of numerous technical and environmental
processes. Often monitoring the flow and species concentrations within the
domain is not possible or is expensive, in contrast, outlet concentration is
straightforward to measure. In connection with reactive flows in porous media,
the term breakthrough curve is used to denote the time dependency of the outlet
concentration with prescribed conditions at the inlet. In this work we apply
several machine learning methods to predict breakthrough curves from the given
set of parameters. In our case the parameters are the Damk\"ohler and Peclet
numbers. We perform a thorough analysis for the one-dimensional case and also
provide the results for the three-dimensional case.
