A particular type of artificial neural network (ANN), with the aim of estimating the indicated pressure into cylinders from instantaneous angular speed measurement, has been developed: radial basis function (RBF). This is the main component of a methodology where input and output curves are parametrized. A modified RBF network from its general structure is designed to reduce the size of the network, approaching the hidden layer weights by means of polynomial functions. It makes it possible to use it in medium requirement PCs, such as in automobile applications. Results corresponding to different operating conditions of a single-cylinder diesel engine (DE), a three-cylinder spark ignition engine (SIE), and a 16-cylinder vee power plant DE (V-16 DE) are presented. Results show the accuracy and fast response of the network, making it feasible to use in online diagnostics and control systems in engines, with very low cost (removing the use of piezoelectric sensors).