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Learning remains at top priority for educators in all the times, whereas some students become good learners and some do not. The reason behind the disparity in students’ performance may result from the diversity of cognitive and learning styles of students besides other demographic factors. The diverse learning needs of learners lead psychologists to focus on the mechanism of learning and to explore ways to make the teaching learning process more effective. The unique cognitive styles and preferred learning styles of learners allow the individuals to optimize their academic strengths. The main purpose of this study was to assess the cognitive styles and learning styles of university students belonging to different areas of specialization. This inquiry was also intended to explore the relationship of these styles with the students’ academic performance and other different demographic variables. Régnier’s Cognitive Style Questionnaire and Kolb’s Learning Style Inventory were used for assessment of cognitive styles and learning styles of university students, respectively. The demographic information of the respondents was collected by using another questionnaire. The sample of the study comprised 1023 respondents, who were female and male graduate students belonging to 24 different fields of study from University of the Punjab, Pakistan. They were mostly unmarried within the age group of 19-24 years, and belonged to urban, sub-urban and rural areas. The information collected by the demographic questionnaire included age, gender, marital status, domicile, family size, field of study, medium of instruction at school level, and academic scores obtained at secondary, intermediary and university level examinations. The treatment and analysis of data were performed by using the software SPSS 16 and the Software C.H.I.C. for the Implicative Statistical Analysis. It is revealed that the respondents displayed 80 different types of cognitive profiles among the 81 potential profiles of the four selected cognitive styles (number of possible profiles: 34). For each cognitive style most of the students showed visual, reflexive/impulsive mixed, focusing, and field dependent/field independent mixed cognitive style dimensions. It was also revealed that the majority of the sample students showed a diverging learning style followed by the assimilating learning style. Comparison across gender showed that female students have more association with all learning styles than do male students. Marital status, age and domicile of students were not related to cognitive style and learning style preferences. Students’ ‘field of study’ and ‘medium of instruction at school level’ were related to learning and cognitive styles. Learning styles have a significant relationship with reflexive, impulsive, and reflexive/impulsive mixed cognitive style of respondents. The grades obtained in secondary school level examinations were significantly associated with learning styles and auditory/visual cognitive styles. However, the marks obtained at intermediary and university level examinations showed no significant relationship with the learning styles and cognitive styles. The converging and assimilating learning styles were strongly associated with academic grades of high achievers while the diverging style has a strong association with performance of low and average achievers. The academic achievement is significantly different at secondary and the intermediary levels in relation to learning styles. The high, average and low achievers have no significant association with cognitive styles. This leads towards the need of content analysis of question papers used for the assessment of academic performance. This study should also be replicated at specific schools, colleges and universities in different provinces of the country to identify the cognitive and learning styles in different cultures.