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Learning Vector Quantization (LVQ) is implemented to classify fetal heart rates into 3 (three) classes: Normal, Suspect, and Pathologic. Normalized data is then divided into 2 (two) parts: training data and testing data. Training data is used to determine the center value and LVQ calculation weight, which later will be used for the classification of testing data. Furthermore, the training data is divided into 3 (three) sections based on real classification, then the average value of each part is then determined. The average value of each section becomes the center value for each class. After conducting training and testing with LVQ, the resulting accuracy is 86% while the error is 14%.