This paper introduces lazification, a code transformation technique that replaces strict with lazy evaluation of function parameters whenever such modification is deemed profitable. The transformation is designed for an imperative, low-level program representation. It involves a static analysis to identify function calls that are candidates for lazification, plus the generation of closures to be lazily activated. Code extraction uses an adaptation of the classic program slicing technique adjusted for the static single assignment representation. If lazification is guided by profiling information, then it can deliver speedups even on traditional benchmarks that are heavily optimized. We have implemented lazification on LLVM 14.0, and have applied it on the C/C++ programs from the LLVM test-suite and from SPEC CPU2017. We could observe statistically significant speedups over clang -O3 on some large programs, including a speedup of 11.1% on Prolang's Bison without profiling support and a speedup of 4.6% on SPEC CPU2017's perlbench (one of the largest programs in the SPEC collection) with profiling support.