The demand for electric power consistently increases for internal combustion engine (ICE) vehicles, as the number of electric components grows in the vehicles. In effect, this causes an increase in fuel consumption when charging their batteries. Therefore, research on an energy management system that can limit such increases in fuel consumption is necessary. In conventional electric systems for vehicles, the alternator is controlled by a feedback system that uses battery State Of Charge (SOC). In order to reduce fuel consumption, the application of extra engine power is important. However, it is difficult to utilize extra engine power in the conventional system. In order to overcome such limitations in conventional systems, in this paper, we propose a predictive energy management strategy based on a rule-based alternator control mode switch. The strategy progresses in two stages. In the first stage, driving information is predicted based on a stochastic model that is derived from the driving database. The predicted information is then used to confirm extra engine power capacity. In the second stage, an alternator control mode switch is operated based on the results of first stage. There are three main modes for the switch: normal charge mode, high-rate charge mode, and low-rate charge mode. In the normal charge mode, the alternator operates in the same manner as it would in a conventional system. When there is extra engine power, the mode is switched to the high-rate charge mode. In this mode, the amount of electric power generation increases. Lastly, in the low-rate charge mode, the alternator supplies minimum operating capacity. This strategy allows for the effective usage of the extra engine power, and as a result, it reduces additional fuel consumption. The performance of the proposed strategy is validated through simulation results.