We present a new algorithm for constructing floating astronomical timescales with explicit uncertainty estimates from sedimentary sequences. The method integrates probabilistic spectral analysis with inverse geochronological modeling, applied to ultra-high-resolution, multiproxy datasets such as core scanning X-Ray Fluorescence (XRF) elemental records. Our framework does not smooth data or impose layer-to-layer dependency, allowing sedimentation rates to vary abruptly at short stratigraphic length scales. By detecting and statistically constraining Milankovitch cycles preserved in stratigraphic signals, the algorithm seeks a floating age-depth model that can be anchored to astronomical tie points, where available. The resulting timescales enable precise, uncertainty-bounded timing of biostratigraphic zones, geochemical events, and depositional cycles. This approach advances astrochronology by combining cycle detection with formal stratigraphic modelling, while preserving fine-scale depositional variability, offering a reproducible and statistically rigorous framework for dating deep-time records.