The exchange of goods between countries is growing, contributing to the promotion of logistics-related technologies. More and more systems are adopting advances in science and engineering to reduce manual handling steps, thereby reducing transit time. Letter-of-Credit (LOC) is a standard method where the parties involved will enter into agreements for the sale and exchange of goods. Specifically, each party will receive a set of original documents and does not need to meet face-to-face under the bank's witness. The process brings many benefits in terms of time and reduces records processing. However, the system faces a lot of risks when one of the parties is dishonest. On the other hand, the traditional LOC systems face a lot of risks related to the transparency of information about the goods, and also the supplier may lose the goods (e.g., 4/100 Vietnamese cashew nut containers are lost. stuck in Italy) or deposits in the hands of shipping companies (e.g., GNN Express -Vietnam) and many more. To this end, many research directions have exploited blockchain technology and smart contracts. Specifically, all information related to the transaction between the supplier and the demander including package, time, and delivery location. However, there needs to be a mechanism to ensure the smooth implementation of smart contracts, specifically for sanctioning when there is a conflict between a supplier and a demander. This role should be considered for the transaction manager, who directly designs and is responsible for their smart contracts. Currently, there is no mechanism to guarantee all interests of the parties involved in non-bank transactions. To increase the processing capacity and integrate with the Blockchain system, we propose the Letter-of-credit Chain that defines the agreements between the parties in international trade. We also deploy the proof-of-concept of the Letter-of-credit Chain on the three EVMsupported platforms (i.e., under ERC20), namely, Ethereum, Binance Smart Chain, and Fantom. By evaluating the actual execution of Gas for each platform, we found that our proposed model had the cheapest fee when deployed on the Fantom platform. Finally, we share the deployment/implementation of these platforms' proof-of-concept to encourage further future research.