A lab-scale continuous ohmic heating (COH) system was developed, and its performance was studied for pineapple juice heating as a model sample. The effect of independent parameters [°Brix/Acid (unstandardized, 18, 22, 26) and flow rate (80–120 mL/min) of juice and electric field strength (EFS: 25–45 V/cm)] were analysed for responses viz. come-up-time, heating rate (HR) and system performance coefficient (SPC). The full factorial experimental design was used for this study. The results showed that with an increase in °Brix/Acid, the % acidity and electrical conductivity decreased significantly (p < 0.05); thus, the come-up-time to reach 90 °C increased significantly. The HR was significantly (p < 0.05) influenced by °Brix/Acid and EFS but less so by flow rates at higher EFS. The SPC was more than 0.90 and reduced significantly (p < 0.05) with an increase in °Brix/Acid and flow rate. The HR was modeled using a feed-forward back-propagation artificial neural network (ANN) with the best topology of 3, 5, and 1 neurons in the input (independent), hidden, and output (response) layers, respectively. The model performed efficiently, which is evident from the high R2 (0.998) and low RMSE (1.255). Thus, the COH, with its high efficiency and HR, can effectively be used to process fruit juice.