We present a framework for run-time parallelism adaptation of multithreaded applications in multi-core systems. Multi-core systems often execute diverse workloads of multithreaded programs with different system resource utilizations and varying levels of parallelism. As a result, the availability of system resources for individual components of the workloads changes at run-time in an unpredictable manner. Consequently, the level of statically determined parallelism by the system infrastructure, e.g. number of concurrent threads, could be suboptimal and lead to performance degradations. The proposed framework monitors the dynamically changing shared system resources, such as the available processor cores, and adapts the number of threads used by the applications throughout a parallel loop execution so as to match the parallelism level to the changed state of the system resources. The end result is the elimination of sizable overheads due to improper level of parallelism, and the resultant serialization of threads on a single core, that could easily occur in a dynamic system environment.