Picrites, dominantly composed of highly forsteritic olivine, can serve as important constraints on primary magma composition and eruption dynamic processes in global Continental Flood Basalt (CFB) provinces.Picrites are commonly divided into high-Ti and low-Ti groups based on whole-rock TiO2 content or Ti/Y ratio. Here, we use an Artificial Neural Network (ANN) to classify the individual olivine in picrites from global CFB provinces according to whether their parental magma is high-Ti or low-Ti to better understand the primary origin and magmatic processes.After training the ANN on one thousand olivine major element compositions data points, the network was able to differentiate chemical patterns for high-Ti and low-Ti olivine, and classify olivine into correct types with an accuracy of >95 %. Moreover, we find that two types of olivine mix in some single samples from Etendeka, Emeishan, and Karoo CFB provinces. Combining the results with chemical markers of source This is the peer-reviewed, final accepted version for American Mineralogist, published by the Mineralogical Society of America.The published version is subject to change. Cite as Authors (Year) Title. American Mineralogist, in press.