We present PRIME (PSF Reconstruction and Identification for Multi-sources characterization Enhancement) as a novel hybrid concept to improve the PSF estimation based on Adaptive optics (AO) control loop data. PRIME uses both focal and pupil plane data to jointly estimate the model parameters, which are both the atmospheric (C 2 n (h), seeing), system (e.g. optical gains, residual low-order errors). The parametric model in use is flexible enough to be scaled with field location and wavelength, making it a proper choice for optimized on-axis and off-axis data-reduction across the spectrum. We review the methodology and on-sky validations on NIRC2 at Keck II. We also present applications of PSF model parameters retrieval using PRIME: (i) calibrate the PSF model for observations void of stars on the acquired images, i.e. optimize the PSF reconstruction process (ii) update the AO error breakdown mutually constrained by the telemetry and the images in order to speculate on the origin of the missing error terms and evaluate their magnitude (iii) measure photometry and astrometry in stellar fields.