Laser capture microdissection (LCM) enables the precise isolation of morphologically defined cell populations, overcoming the confounding effects of tissue heterogeneity in DNA methylation analyses. However, the low DNA yield inherent to LCM—often derived from fewer than 1000 cells—challenges conventional bisulfite-based sequencing, which requires high DNA input and induces severe degradation. Here, we integrate LCM with Enzymatic Methyl-seq (EM-seq), a bisulfite-free, enzymatic conversion method that preserves DNA integrity by minimizing damage and reducing GC bias. Our optimized low-input library preparation protocols allow robust and reproducible methylation profiling from as few as 100 cells, with data quality comparable to that of bulk tissue samples. This strategy not only enables the isolation of tumor cells to uncover methylation signatures for early biomarker discovery and targeted therapies in oncology but also holds promise for advancing personalized medicine through patient-specific epigenetic profiling. Overall, our work establishes LCM-EM-seq as a scalable framework for spatially resolved, methylation-aware analyses of rare cell populations, opening new avenues for studying epigenetic heterogeneity in development and disease.