Anti-lock Brake System (ABS) is an active safety system nowadays implemented in every new car and could prevent the wheels from locking during heavy braking. Steering becomes ineffective and the brake distance longer than necessary when the wheels are locked. ABS has reduced the amount of non-fatal crashes significantly, but there are still situations in which it can control worse than driver would himself. For example, when driving on low-friction roads. The aim in this thesis is to develop a new ABS algorithm using potentially available information about wheel forces. Data of wheel forces is currently not measured in consumer cars, but SKF is developing load sensing bearings which could be feasible for such cars. The sensor output provides more directly relevant information than wheel deceleration data does. The latter is used in current ABS technology. A novel ABS algorithm that uses both force and wheel slip measurements for control is designed. The algorithm is validated on a Simulink model consisting of Delft-Tyre, simplified actuator dynamics, (optional) sensor noise, and a quarter car model. An EKF based on the Burckhardt model acts as reference for the control algorithm. The Burckhardt model is a computationally lightweight formula and allows the EKF to be used on-line against relatively little computational cost. Friction estimation is essential in the designed ABS algorithm, as it is dependant on the road surface which is not known a priori. The designed algorithm is first assessed in a Simulink model on different road surfaces. Field tests are performed as well. They show that the combination of force and slip measurements is indeed promising. On-line estimates using the EKF are found sufficiently accurate to be used as main reference for the controller.