The total electron content (TEC) over the Iberian Peninsula was modeled using a PCA-based models based on the decomposition of the observed TEC series using the principal component analysis (PCA) and reconstruction of the daily modes’ amplitudes either by a multiple linear regression model (MRM) or neural networks (NN) using several types of space weather parameters as regressors/predictors: proxies for the solar UV and XR fluxes, number of the solar flares of different types, parameters of the solar wind and of the interplanetary magnetic field, and geomagnetic indices. Lags of 1 and 2 days between the TEC and space weather parameters are used. The general performance of the PCA-MRM and PCA-NN models is tested for different months and in different space weather conditions.