This chapter focuses on the estimation of car dynamic variables for the improvement of vehicle safety, handling characteristics and comfort. More specifically, a new estimation process is proposed to estimate longitudinal/lateral tire-road forces, velocity, sideslip angle and wheel cornering stiffness. One main contribution of the process is that it uses measurements from currently available standard sensors (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities). Another contribution is that the process provides robust sideslip angle estimations with respect to cornering stiffness changes (or tire-road friction variations). Finally, the estimation process is applied and compared to real experimental data, notably sideslip and wheel force measurements. The last few years have seen the emergence in cars of active security systems to reduce dangerous situations for drivers. Among these active security systems, Anti-lock Braking Systems (ABS) and Electronic Stability Programs (ESP) significantly reduce the number of road accidents. However, these systems may be improved if the dynamic potential of a car is well known. For example, information on tire-road friction means a better definition of potential trajectories, and therefore a better management of vehicle controls. Nowadays, certain fundamental data relating to vehicle-dynamics are not measurable in a standard car for both technical and economic reasons. As a consequence, dynamic variables such as tire forces and sideslip angle must be observed or estimated. Vehicle-dynamic estimation has been widely discussed in the literature, e.g. (Kiencke & Nielsen, 2000), (Ungoren et al., 2004), (Lechner, 2002), (Stephant et al., 2006), (Baffet et al, 2006a). The vehicle-road system is usually modeled by combining a vehicle model with a tire-force model in one block. One particularity of this study is that it separates the estimation modeling into two blocks (shown in Figure 1), where the first block concerns the car body dynamic while the second is devoted to the tire-road interface dynamic. The first block contains an Extended Kalman Filter (denoted as