  In this work, a heuristic as operational tool to estimate the lactate
threshold and to facilitate its integration into the training process of
recreational runners is proposed. To do so, we formalize the principles for the
lactate threshold estimation from empirical data and an iterative methodology
that enables experience based learning. This strategy arises as a robust and
adaptive approach to solve data analysis problems. We compare the results of
the heuristic with the most commonly used protocol by making a first
quantitative error analysis to show its reliability. Additionally, we provide a
computational algorithm so that this quantitative analysis can be easily
performed in other lactate threshold protocols. With this work, we have shown
that a heuristic %60 of 'endurance running speed reserve', serves for the same
purpose of the most commonly used protocol in recreational runners, but
improving its operational limitations of accessibility and consistent use.
