At present, the Occupational Accident Labor Insurance premium rate is calculated based on the business categories in Taiwan. The premium rate is calculated as a combination of the experience rate and the manual rate for each business category. The traditional actuarial methods are based on many hypotheses to calculate future actual claims and adjust the rate for each business category. Unfortunately, with such adjustments, the risk level of the insured in the business category will be affected. To accurately estimate the size of actual losses for specific industries, we propose a genetic algorithm applied grouping to determine the premium rate for occupational accidents. The proposed approach has been evaluated using the real-world dataset from the Bureau of Labor Insurance in Taiwan that includes occupational accident insurance data from 2009 to 2015. The results demonstrate that the method is practicable at predicting the applicable premium. The proposed method differs from Taiwan's prevailing occupational accident premium rate calculation method. Moreover, it is efficient at selecting the best group of the Standard Industrial Classification from the genetic algorithm. Lastly, the accuracy of the estimates of the total claim amounts are analyzed.