The paper presents the test results of the accuracy and repeatability of the three-axis milling plotter with the use of the LSP 30 Compact laser interferometer. The experiment was carried out using two measurement strategies. A machine learning (ML) model was developed using feed rate vf and the positioning accuracy and repeatability parameters (A, A↑A↓, R, R↑R↓, B and B). Due to the nature of the data, a linear regression model was chosen. A less efficient but more accurate measurement strategy was the ´pilgrim´ strategy. Whereas, the linear measurement strategy proved to be more efficient but less accurate. High, constant insolation of the test stand and air humidity influenced the measurement results. The predicted positioning accuracy and repeatability parameters were determined on the basis of the developed model using first-degree regression equations. Prediction of positioning accuracy parameters depending on measurement conditions and measurement strategies can be a useful tool to control or predict the process machine accuracy and the shaped contour accuracy.