<p>Chronic pain is a severe burden affecting 20% of the population worldwide. To develop novel analgesics, in vivo preclinical assessment of the pain threshold is inevitable. Investigation of the nociception in rodents is still challenging, since most of the currently available methods are manually operated. So, the results highly depend on the experience of the examiner and can be significantly biased by subjective human factors. To improve this translational research paradigm, advanced tools are needed in this field. Therefore, the aim of the present study was to develop a new generation automated pain assessment device. In collaboration with Z-Elektronika Ltd., Pécs, Hungary we have designed and validated high-precision automated dynamic plantar aesthesiometer (ADPA) that is suitable for the assessment of mechanonociceptive threshold in rats and mice. It utilizes artificial intelligence (AI) to automatically recognize the animals investigated. The system’s software controls the mechanical stimulation of the hindpaws with simultaneous video recording of the nocifensive reaction and analysis of the pain thresholds. The main advantage of ADPA is the automated, computer-controlled induction and evaluation of the pain threshold, increasing the quality, comparability, reproducibility, and objectivity of the results. This device may significantly enhance the accuracy of pain assessment in animal models and contribute to improved preclinical pain research.</p>