Multiple lines of research in ice core science are limited by manually intensive and time-consuming optical microscopy investigations for the detection of insoluble particles, from pollen grains to volcanic shards. To help overcome these limitations and support researchers, we present a novel methodology for the identification and autonomous classification of ice core insoluble particles based on flow image microscopy and neural networks.