Langmuir probes have been extensively studied theoretically, and used experimentally to infer plasma parameters, such as density and temperature, in laboratory and space plasma. Because of their small size and relative simplicity, these probes are used to diagnose plasma in most laboratory experiments and many space missions. Despite the apparent simplicity, however, the task of inferring accurate physical parameters with Langmuir probes remains notoriously challenging. Aside from technical aspects related for example, to calibration and surface condition, one difficulty is that the inference of plasma parameters from probe measurements requires the solution of a complex inverse problem. The direct problem in which a characteristic; that is, current as a function of bias voltage, is calculated for known plasma conditions, is now relatively easy to solve numerically, by accounting for the relevant physical processes and measurement conditions. The inverse problem however, is significantly more daunting, owing the large computation time required to carry out simulations, and the several iterations required to interpret a single characteristic. This is why the inference of plasma parameters from Langmuir probe characteristics has so far relied almost exclusively on analytic models, leading to fast and simple algorithms capable producing answers in near-real time. In order to be tractable analytically, however, theoretical interpretive models cannot account for several of the conditions under which measurements are made, and they must rely on assumptions that are seldom fully satisfied in an actual experimental setup. This in turn can lead to significant uncertainties in the inferred density or temperature. In our approach we use three-dimensional kinetic simulations to compute probe characteristics for a set of representative plasma parameters, while accounting for more realistic geometry than possible analytically. Solution libraries, or in machine learning parlance training data sets, are then constructed from which empirical analytic inversions algorithms can be derived. The physics of current collection by electric probes immersed in plasma was described in seminal articles by Mott-Smith and Langmuir (1926), and Tonks and Langmuir (1929) nearly a century ago. These papers defined the basis of the "Orbital Motion" theory for spherical and cylindrical probes, now referred to as "Orbital Motion Limited" or OML theory, which has since been used to infer plasma density and temperature in many laboratory, and more recently, in space plasma experiments. Several assumptions are made in the OML theory, in order to obtain analytic solutions, including (i) a spatially uniform plasma background, (ii) negligible collisions and magnetic field, (iii) probe radii much smaller than the Debye length, and (iv) for a cylindrical probe, a length much larger than the Debye length in order for end effects to be Abstract A novel approach is presented to infer plasma parameters from Langmuir probe measurements. Three-dimensional kinetic...