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The selection mechanism for method invocation binding is a cornerstone of object-oriented programming (OOP) language design, embodying the fundamental trade-off between execution performance (early/static binding) and architectural flexibility (late/dynamic binding). While the theoretical dichotomy is well-established, a significant gap exists in the literature regarding the quantified impact of these mechanisms on contemporary microarchitectures featuring deep cache hierarchies, advanced indirect branch predictors, and sophisticated just-in-time (JIT) compilation environments. This study presents a rigorous, multi-language benchmarking analysis to dissect the performance characteristics of method dispatch. We evaluate C++, Java, and Rust on both x86-64 and ARMv8 (Apple M2) platforms, measuring dispatch latency, memory overhead, cache behaviour, and scalability across varying inheritance depths and polymorphic widths. Our results indicate that while late binding introduces a baseline overhead of 3–6 ns—a 3–4x increase over early binding's sub-nanosecond latency—this penalty is highly non-linear. We demonstrate that polymorphic width (number of implementations) is the dominant performance scaling factor, with 100 implementers causing a 175% latency increase due to branch mis-prediction, compared to a modest 27% increase for a depth of 10 levels. Furthermore, we quantify the efficacy of modern compiler optimizations, showing that de-virtualization and inlining can eliminate dispatch overhead in up to 73% of statically monomorphic contexts. Finally, we extend our analysis to emergent domains, quantifying dispatch overhead in AI inference frameworks and energy consumption, providing a data-driven taxonomy to guide software architects in making informed binding decisions.