Approximate reasoning is one of the most effective fuzzy systems. The compositional rule of inference founded on the logical law Modus Ponens is furnished with a true conclusion, provided that the premises of the rule are true as well. One of the premises is formed as the implication, which is represented by different mathematical approaches, but we are especially fond of the results brought by the early implication proposed by Zadeh, which is modified in our practical model concerning a medical application. The approximate reasoning system, grounded on the extended and modified version of Modus Ponens law, will be employed here to predict a chance of survival after the operation for a patient who suffers from cancer. The patient’s symptom levels are the indicators of the disease. If the symptoms do not exceed their critical values there is still a chance to save the patient’s life by trying surgery. We wish to evaluate the verbal prognosis of the surgery by involving specifically designed fuzzy sets in the algorithm of approximate reasoning. Since the chance of successful surgery depends on the interactions of several symptoms then we will name the decision model multi-dimensional.