The strontium isotope signature (87Sr/86Sr) of calcite precipitated in rock fractures and faults is a frequently used tool to trace paleofluid flow. However, bedrock fracture networks, such as in Precambrian cratons, have often undergone multiple fracture reactivations resulting in complex sequences of fracture mineral infillings. This includes numerous discrete calcite crystal overgrowths. Conventional 87Sr/86Sr analysis of dissolved bulk samples of such crystals is not feasible as they will result in mixed signatures of several growth zonations. In addition, the zonations are too fine-grained for sub-sampling using micro-drilling. Here, we apply high spatial resolution 87Sr/86Sr spot analysis (80 µm) in transects through zoned calcite crystals in deep Paleoproterozoic granitoid fractures using laser ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) to trace discrete signs of paleofluid flow events. We compare the outermost calcite growth zone with 87Sr/86Sr values of the present-day groundwater sampled in the same boreholes to distinguish potential modern precipitates. We then connect our results to previously reported radiometric dating and C and O isotope signatures to understand the temporal history and physicochemical evolution of fluid flow within the fractures. Comparisons of modern calcite precipitated in a borehole over a period of 17 years with modern waters prove the concept of using 87Sr/86Sr as a marker for fluid origin in this environment and for how 87Sr/86Sr changed during marine water infiltration. Intermittent calcite precipitation over very long time spans is indicated in calcite of the currently open fractures, showing an evolution of 87Sr/86Sr from ~0.705–0.707—a population dated to ~1.43 billion years—to crystal overgrowth values at ~0.715–0.717 that overlap with the present-day groundwater values. This shows that high spatial resolution Sr isotope analysis of fine-scaled growth zonation within single calcite crystals is applicable for tracing episodic fluid flow in fracture networks