The complex non-linear regime of the monthly rainfall in Catalonia (NE Spain) is analyzed by means of the reconstruction fractal theorem and the multifractal detrended fluctuation analysis algorithm. Areas with a notable degree of complex physical mechanisms are detected by using the concepts of persistence (Hurst exponent), complexity (embedding dimension), predictive uncertainty (Lyapunov exponents), loss of memory of the mechanism (Kolmogorov exponent), and the set of multifractal parameters (Hölder exponents, spectral asymmetry, spectral width, and complexity index). Besides these analyses permitting a detailed description of monthly rainfall pattern characteristics, the obtained results should also be relevant for new research studies concerning monthly amounts forecasting at a monthly scale. On one hand, the number of necessary monthly data for autoregressive processes could change with the complexity of the multifractal structure of the monthly rainfall regime. On the other hand, the discrepancies between real monthly amounts and those generated by some autoregressive algorithms could be related to some parameters of the reconstruction fractal theorem, such as the Lyapunov and Kolmogorov exponents.