This study was conducted to develop a simple volume model for the Larix kaempferi species in the Central Region of South Korea. General volume model forms were used and validated using a subset of the data collected for the L. kaempferi species. A total of 550 trees were collected in the different L. kaempferi stands through destructive sampling. The dataset was randomly divided into two: 80% for initial model development(seven volume models) and 20% for model validation. The 100% dataset was used for the final model fitting. Evaluation statistics including bias(Ē), absolute mean deviation(AMD), root mean square error(RMSE), coefficient of determination(R2), and the Akaike Information Criterion values(AIC) and weight (AICw) were used to assess performance of the different volume models. Rank analysis was employed and the first five best volume models were chosen for the model validation and final model fitting. The evaluations showed that volume model 4(V=aDBHb*Hc) had the best performance, while volume model 3(V=aDBH+bDBH2), which has a single variable, had the poorest performance.