All-terrain forklift trucks often work on complex terrain such as soft and muddy terrain in the wild, making them prone to rolling and rollover. In this work, a seven-degree-of-freedom nonlinear dynamic model and a wheel-ground interaction model between resilient wheels and soft/hard road surfaces based on the structural characteristics of the articulated steering + swinging bridge of an all-terrain forklift truck are established. The mechanism of all-terrain forklift trucks’ roll instability and a simulation comparison of four types of road models (rigid, sandy, loam, and clay) are analyzed. All-terrain forklift trucks are least prone to rolling when being driven on rigid roads. On soft roads, sand brings the greatest risk of rollover, followed by loam and clay. The roll stability indexes HR-LTR and SR-LTR considering different road surfaces are proposed. The safety limit of roll stability based on the indexes is divided, and an anti-rollover control strategy based on road surface recognition is proposed. On the basis of the road surface recognition results, corresponding stability index calculation methods and actuator control algorithms are selected. Simulation and experimental results show that with the use of no control and TTR-based hierarchical control, the forklift truck yaw velocity is reduced by up to 73.31% and 63.52%, respectively, and the roll angle is reduced by up to 72.7% and 48.27%, respectively. The proposed roll stability index and anti-rollover control strategy for different road surfaces can effectively improve the roll stability of all-terrain forklift trucks when being driven on different complex road surfaces, reduce the risk of rollover, and improve the rollover stability of all-terrain forklift trucks on different complex roads, thereby improving the safety of all-terrain forklift trucks.