Papaya is one of the fruits that grows in the tropics area, one of the kinds that people’s love the most is papaya California. The quality identification of papaya California fruit can be measured using color, defect, and size. Color, defect and size extracted from image of papaya. The dataset that used in this research are 150 images papaya California. The dataset consist of 3 quality there are good, fair and low. Identification of papaya using the backpropagation neural network method with 17 training function in each training data with 3 different neurons in the hidden layer. The best result of the test is using training function trainrp with 10 neurons is 81,33% for accuracy, 73,37% for precision, and 72% for recall, with 20 neurons is 82,67% for accuracy, 75,24% for precision, and 74% for recall, and with 25 neurons is 80,89% for accuracy, 74,42% for precision, and 71,33% for recall.