This study attempts to develop a joint framework model that simultaneously estimates the mode choice and shipment size choice for inter-city freight. The disaggregated dataset of intercity freight from the Japan Commodity Flow Survey (CFS) and the Level of Service (LOS) data from NITAS were used in estimating the parameters of the model. A logit mixture model was developed using the variables of time, cost, distance, and the number of employees. The framework was then utilized in analyzing the model parameters and computed elasticities for the chemical, metal and machinery, and light industrial commodities. The models that were developed highlight the importance of considering the transport mode and shipment size simultaneously, validating the results of pasts studies. Insights from the parameter estimation show that different industries have different behaviors regarding the correlation of error components among the alternatives. The computed elasticities indicate that there will be a change in the probabilities of shipment size distribution when there is a shift in mode choice.