Due to its applicability in numerous machine learning and computer vision applications, handwritten digit identification has lately grown in significance and attracted a large number of researchers. This project uses a variety of machine learning approaches to recognise Dzongkha characters written by hand. The main driving force behind this effort is the absence of the Dzongkha handwritten digit dataset. We have gathered data on Dzongkha handwriting digit from indigenous and non-indigenous persons in Bhutan to make it easier to recognize Dzongkha handwritten characters, and we have made the dataset available for further study. Additionally, we have employed a number of machine learning methods, such as the support vector machine, K-nearest neighbour, and decision tree. With an accuracy of 98.29%, the support vector machine classification algorithm has excelled among these algorithms. Dataset Link: https://zenodo.org/record/6271560 Paper Link: Will be updated, when online.