Systems for diagnosing and predicting failures have become an integral part of various industrial sectors. In addition to providing protection, their application has contributed to advancements in planning and implementing changes to minimize the impact of potential failures on results and efficiency. Ultimately, automation has increased the precision of machine operation analysis, leading to more efficient predictions of future failures, the development of safe working conditions, and economic sustainability. In the first part of the paper, the theoretical framework provides insight into methods for monitoring the system's condition and various sensors suitable for use in the prediction and diagnosis of failures. The second part of the paper is dedicated to the development of a custom system for diagnosing and predicting failures, based o n a compiled list of requirements. An example involving the operation of an electric motor that drives a gear through a shaft is taken, and this example includes monitoring the condition of vibrations on the shaft, the temperature of the electric motor, and the temperature of the bearings. The software package used for creating an automatic diagnostic and failure prediction system is Logo Soft Comfort. Finally, the paper concludes with a reflection on the designed system example, highlighting the assistance and efficiency that is ensured and enabled through the use of Logo Soft Comfort software.