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The research objective is to develop a monitoring system for the growth of red spinach plants based on image processing techniques from images captured using multiple cameras. The plant used is red spinach (Amaranthus gangeticus L.). Three cameras are installed in the top, side and front position of the plants in the photo box with lighting every 2 days up to 39 days. Model development uses a sample of 236 plants divided into 178 plants for model development and 58 plants for model testing every two days. The model is tested with the coefficient of determination (R2) to measure how much the independent variables ability to explain the dependent variable. The network architecture consists of three input neurons, first hidden layer with five neurons, second hidden layer with five neurons, and output layers with one neuron. The function of ANN with value of the learning level is 0.001. The activation function to predict fresh weight and leaf area of plants is tansig-logsig-tansig and tansig-tansig-logsig. ANN model can predict fresh plant weight with MSE value of 0.02385 and RMSE of 0.154, while for leaf area MSE value of 0.26428 and RMSE of 0.514.