Classification is a first-line tool for understanding the main characteristics of a natural system's response. We propose a new classification of karst systems hydrological functioning that is based on spring discharge time series and takes profit of spring discharge databases to encompass the high diversity of karst hydrological functioning. It discriminates six different classes based on three relevant indicators of karst hydrological functioning. A core dataset made of 10 karst systems was first considered for the setup of the classification. The spring discharge time series were investigated according to recession curves, statistical and signal analyses to identify relevant indicators of hydrological functioning. The selection of the most relevant indicators and the proposal of the classification were based on multivariate analyses. The classification was then tested on spring discharge time series of 78 karst systems located worldwide. All the systems homogeneously spread among the six proposed classes, which highlights the relevance of the approach and the representativeness of the various classes of hydrological functioning. Results from the proposed methodology were finally discussed to explore its limitations and define guidelines for its application.