Slip prediction is important for maintaining the stability of object handling in robust grasping and dexterous manipulation. However, up to date a challenge still remains that how to accurately predict slip occurrence before it actually happens to allow robotic hands to conduct slip compensation in time. The concept of friction cone has been conventionally used to predict slip occurrence, where the static/kinetic friction coefficient is used as a threshold. However, this threshold, i.e. the ratio of the friction and normal forces at slip occurrence (also named as break-away friction ratio), is found not constant but varies with changes in acceleration and disturbing forces applied on the grasped object, raising difficulties when attempting to accurately predict slip. In this paper, we propose a novel approach to accurately predict varying slip thresholds in real time and compensate the predicted slip during a dynamic grasping. To achieve this, first a simple but efficient haptic surface exploration using robotic fingers is carried out to identify the friction properties of an object surface. Once the friction properties are established, the slip threshold at a given grasping condition can be predicted and the grasping forces are adjusted to prevent slip. The presented approach has been evaluated, showing good performance in terms of prediction accuracy and computational efficiency.