Mechanistic-Empirical  (M-E)  pavement  design  procedures  are  composed  of  a  reliable  response model to estimate the state of stress in the pavement and distress models in order to predict the different types of pavement distresses due to the prevailing traffic and environmental conditions. One of the main objectives of this study was to develop a response model based on multilayer elastic  theory   (MLET)  with  improved  computational  performance  by   optimizing  the   time consuming parts of the MLET processes. A comprehensive comparison of the developed program with  two  widely  used  programs  demonstrated  excellent  agreement  and  improved  computational performance.  Moreover,  the  program  was  extended  to  incorporate  the  viscoelastic  behaviour  of bituminous materials through elastic-viscoelastic correspondence principle. A procedure based on collocation of linear viscoelastic (LVE) solutions at selected key time durations was also proposed that improved the computational performance for LVE analysis of stationary and moving loads. A comparison  of  the  LVE  responses  with  measurements  from  accelerated  pavement  testing  (APT) revealed a good agreement. Furthermore the developed response model was employed to evaluate permanent deformation models  for  bound  and  unbound  granular  materials  (UGMs)  using  full  scale  APTs.  The  M-E Pavement  Design  Guide  (MEPDG)  model  for  UGMs  and  two  relatively  new  models  were evaluated  to  model  the  permanent  deformation  in  UGMs.  Moreover,  for  bound  materials,  the simplified  form  of  the  MEPDG  model  for  bituminous  bound  layers  was  also  evaluated.  The measured  and  predicted  permanent  deformations  were  in  general  in  good  agreement,  with  only small discrepancies between the models. Finally, as heavy traffic loading is one of the main factors affecting the performance of flexible pavement, three types of characterizations for heavy traffic axle load spectrum for M-E analysis and design of pavement structures were evaluated. The study recommended an improved approach that enhanced the accuracy and computational performance.