The study of technology to solve the energy demand problem and global warming by replacing gasoline vehicles with electric vehicles is an interesting solution because the electric vehicle (EV) uses an electric motor to drive the powertrain. This research study and evaluation centers on the main factors that influence energy consumption for non-fixed route diesel fuelled buses (fuel bus) and electric buses by using the Artificial Neuro-Fuzzy Inference Systems (ANFIS) method comparing energy consumption saving between the Fuel Bus model and EV model. Metrology to indicate significance factors which affected energy consumption was based on the 403 collected questionnaires that were surveyed from non-fixed route buses around Bangkok. The simulation of fuel and electric bus was created by the Artificial Neuro-Fuzzy Inference Systems (ANFIS) method. The output of this method relates 6 significance factors to energy consumption in units of MJ/km. The result of this study shows that an Electric Bus can save around 76 % in energy consumption compared with a fuel bus. Scenarios were included in the study in which non-fixed route buses more than 10 years old were changed to electric buses defined by percent replacement including 20, 40, 80 and 100 percent. Results showed that replacement can save energy at the rate of 2,000,000 - 12,000,000 GJ/year. However, traffic conditions still affect the energy consumption, as air conditioning in the electric bus consumes around 73% of the total usage.