The fast evolution of hardware demands a continue evolution of the compilers. Compiler designers must perform a tuning process to ensure that the code generated by the compiler maintain a certain quality, both in terms of processing time or another preset feature. This work aims to automate compiler adjustment process through machine learning techniques. As a result the compiler plans obtained using machine learning with the proposed features had produced code for programs whose values for the execution times approached those following the standard plan used by LLVM.