The weight transfer is continuously excited by brake pressure changes during braking with activated ABS. For this reason, the wheel load oscillations become more severe with activated ABS, which makes difficult the manipulation of brake pressure due to wheel slip oscillations and wheel acceleration changes which are control variables for ABS. Thus, this study aims to reduce wheel load oscillations during braking with activated ABS (anti-lock brake system). For this aim, the integration between suspension system and ABS was developed by designing the control strategy based on the results of ABS road tests. ABS tests are conducted on wet and slippery road by using hard and medium-hard stages of same damper to determine the rules of control strategy. The control strategy sets the damper stages according to the build up and reduction rates of measured brake pressure via estimated dynamic wheel load information. Estimation of dynamic wheel load is performed with ANN (artificial neural network) using multilayer perceptron networks. This is a novel approach for determining wheel load changes during braking with activated ABS due to difficulties in measuring of dynamic wheel load. Therefore, the results show that the reductions in wheel load are the most influence method to suppress simultaneously both brake pressure and wheel acceleration. In addition, one of the most important results of this study is that the proposed control strategy shortens the braking distance.